A calculator to predict big-O of sorting functions
Project description
Big-O Caculator
A big-O calculator to estimate time complexity of sorting functions.
inspired by : https://github.com/ismaelJimenez/cpp.leastsq
Installation
pip install big-O-calculator
What it does
You can call which array to test
(n : [10, 100, 1_000, 10_000, 100_000])
Big-O calculator
Methods:
test(function, array="random", limit=True, prtResult=True): It will run only specified array test, returns Tuple[str, estimatedTime]
test_all(function): It will run all test cases, prints (best, average, worst cases), returns dict
runtime(function, array="random", size): It will simply returns execution time to sort length of size of test array, returns Tuple[float, List[Any]]
Args:
functionName [Callable]: a function to call.
array [str]: "random", "sorted", "reversed", "partial", "Ksorted".
limit [bool] = True: To break before it takes "forever" to sort an array. (ex. selectionSort)
prtResult [bool] = True: Whether to print result by itself
Returns:
complexity [str] : ex) O(n)
time [float] : Time took to sort all 5 different arrays in second (maxLen=100,000)
Info:
To see the result of function, return the array.
K in Ksorted will use testSize.bit_length().
Usage
from bigO import bigO
from bigO import algorithm
tester = bigO.bigO()
tester.test(bubbleSort, "sorted")
tester.test_all(bubbleSort)
tester.runtime(bubbleSort)
tester.runtime(algorithm.insertSort)
Quick Sort Example
from bigO import bigO
from random import randint
def quickSort(array): # in-place | not-stable
"""
Best : O(nlogn) Time | O(logn) Space
Average : O(nlogn) Time | O(logn) Space
Worst : O(n^2) Time | O(logn) Space
"""
if len(array) <= 1:
return array
smaller, equal, larger = [], [], []
pivot = array[randint(0, len(array) - 1)]
for x in array:
if x < pivot:
smaller.append(x)
elif x == pivot:
equal.append(x)
else:
larger.append(x)
return quickSort(smaller) + equal + quickSort(larger)
tester = bigO.bigO()
complexity, time = tester.test(quickSort, "random")
complexity, time = tester.test(quickSort, "sorted")
complexity, time = tester.test(quickSort, "reversed")
complexity, time = tester.test(quickSort, "partial")
complexity, time = tester.test(quickSort, "Ksorted")
''' Result
Running quickSort(random array)...
Completed quickSort(random array): O(nlog(n))
Time took: 0.35816s
Running quickSort(sorted array)...
Completed quickSort(sorted array): O(nlog(n))
Time took: 0.37821s
Running quickSort(reversed array)...
Completed quickSort(reversed array): O(nlog(n))
Time took: 0.38500s
Running quickSort(partial array)...
Completed quickSort(partial array): O(nlog(n))
Time took: 0.35820s
Running quickSort(Ksorted array)...
Completed quickSort(ksorted array): O(nlog(n))
Time took: 0.38140s
'''
Selection Sort Example
from bigO import bigO
def selectionSort(array): # in-place, unstable
'''
Best : O(n^2) Time | O(1) Space
Average : O(n^2) Time | O(1) Space
Worst : O(n^2) Time | O(1) Space
'''
currentIdx = 0
while currentIdx < len(array) - 1:
smallestIdx = currentIdx
for i in range(currentIdx + 1, len(array)):
if array[smallestIdx] > array[i]:
smallestIdx = i
array[currentIdx], array[smallestIdx] = array[smallestIdx], array[currentIdx]
currentIdx += 1
return array
tester = bigO.bigO()
complexity, time = tester.test(selectionSort, "random")
complexity, time = tester.test(selectionSort, "sorted")
complexity, time = tester.test(selectionSort, "reversed")
complexity, time = tester.test(selectionSort, "partial")
complexity, time = tester.test(selectionSort, "Ksorted")
''' Result
Running selectionSort(random array)...
Completed selectionSort(random array): O(n^2)
Time took: 4.04027s
Running selectionSort(reversed array)...
Completed selectionSort(reversed array): O(n^2)
Time took: 4.04918s
Running selectionSort(sorted array)...
Completed selectionSort(sorted array): O(n^2)
Time took: 3.97238s
Running selectionSort(partial array)...
Completed selectionSort(partial array): O(n^2)
Time took: 4.02878s
Running selectionSort(Ksorted array)...
Completed selectionSort(ksorted array): O(n^2)
Time took: 4.05617s
'''
test_all(mySort) Example
We can test all "random", "sorted", "reversed", "partial", "Ksorted" by one with test_all method
from bigO import bigO
lib = bigO.bigO()
lib.test_all(bubbleSort)
lib.test_all(insertSort)
result = lib.test_all(selectionSort)
print(result) # Dictionary
''' Result
Running bubbleSort(tests)
Best : O(n) Time
Average : O(n^2) Time
Worst : O(n^2) Time
Running insertSort(tests)
Best : O(n) Time
Average : O(n^2) Time
Worst : O(n^2) Time
Running selectionSort(tests)
Best : O(n^2) Time
Average : O(n^2) Time
Worst : O(n^2) Time
{'random': 'O(n^2)', 'sorted': 'O(n^2)', 'reversed': 'O(n^2)', 'partial': 'O(n^2)', 'Ksorted': 'O(n^2)'}
'''
runtime(mySort) Example
from bigO import bigO
from bigO import algorithm
lib = bigO.bigO()
timeTook, result = lib.runtime(algorithm.bubbleSort, "random", 5000)
''' Result
Running bubbleSort(len 5000 random array)
Took 2.61346s to sort bubbleSort(random)
'''
Built-in algorithms list
Visit here to see codes
BinaryInsertSort, BubbleSort, CountSort, gnomeSort, heapSort, InsertSort, InsertSortOptimized, IntroSort, mergeSort, quickSort(random pivot), timSort(simplified)
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