Modify the quicksort function so that it calls insertion sort to sort any sublist whose size is less than 50 items. Compare the performance of this version with that of the original one, using data sets of 50, 500, and 5,000 items. Then adjust the threshold for using the insertion sort to determine an optimal setting. Use python’s time module to calculate the duration of the original quicksort version and the modified version. Do this for 3 different data sets of 50, 500, and 5000 items. These datasets are not going to be provided, so you have to come up with them. You can use python’s random module to help come up with the random item. Experiment with a different threshold value for the size of the sublist that indicates a switch to insertion sort, and report which value was optimal. Use this template: import time def original_quicksort(input_list): sorted_list = [] #TODO: Your work here # Return sorted_list return sorted_list def modified_quicksort(input_list): sorted_list = [] #TODO: Your work here # Return sorted_list return sorted_list if __name__ == "__main__": my_list = [3, 4, 1, 5, 2] print(original_quicksort(my_list)) # Correct Output: [1, 2, 3, 4, 5] print(modified_quicksort(my_list)) # Correct Output: [1, 2, 3, 4, 5
Modify the quicksort function so that it calls insertion sort to sort any sublist
whose size is less than 50 items. Compare the performance of this version with
that of the original one, using data sets of 50, 500, and 5,000 items. Then adjust the
threshold for using the insertion sort to determine an optimal setting.
Use python’s time module to calculate the duration of the original quicksort version and the modified version. Do this for 3 different data sets of 50, 500, and 5000 items. These datasets are not going to be provided, so you have to come up with them. You can use python’s random module to help come up with the random item. Experiment with a different threshold value for the size of the sublist that indicates a switch to insertion sort, and report which value was optimal.
Use this template:
import time
def original_quicksort(input_list):
sorted_list = []
#TODO: Your work here
# Return sorted_list
return sorted_list
def modified_quicksort(input_list):
sorted_list = []
#TODO: Your work here
# Return sorted_list
return sorted_list
if __name__ == "__main__":
my_list = [3, 4, 1, 5, 2]
print(original_quicksort(my_list)) # Correct Output: [1, 2, 3, 4, 5]
print(modified_quicksort(my_list)) # Correct Output: [1, 2, 3, 4, 5]
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