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move-files-and-2-renames (#4285)
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"""
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Given an array of integer elements and an integer 'k', we are required to find the
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maximum sum of 'k' consecutive elements in the array.
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Instead of using a nested for loop, in a Brute force approach we will use a technique
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called 'Window sliding technique' where the nested loops can be converted to a single
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loop to reduce time complexity.
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"""
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from typing import List
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def max_sum_in_array(array: List[int], k: int) -> int:
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"""
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Returns the maximum sum of k consecutive elements
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>>> arr = [1, 4, 2, 10, 2, 3, 1, 0, 20]
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>>> k = 4
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>>> max_sum_in_array(arr, k)
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24
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>>> k = 10
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>>> max_sum_in_array(arr,k)
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Traceback (most recent call last):
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...
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ValueError: Invalid Input
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>>> arr = [1, 4, 2, 10, 2, 13, 1, 0, 2]
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>>> k = 4
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>>> max_sum_in_array(arr, k)
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27
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"""
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if len(array) < k or k < 0:
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raise ValueError("Invalid Input")
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max_sum = current_sum = sum(array[:k])
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for i in range(len(array) - k):
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current_sum = current_sum - array[i] + array[i + k]
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max_sum = max(max_sum, current_sum)
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return max_sum
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if __name__ == "__main__":
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from doctest import testmod
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from random import randint
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testmod()
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array = [randint(-1000, 1000) for i in range(100)]
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k = randint(0, 110)
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print(f"The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}")
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"""
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Given an array of integer elements and an integer 'k', we are required to find the
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maximum sum of 'k' consecutive elements in the array.
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Instead of using a nested for loop, in a Brute force approach we will use a technique
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called 'Window sliding technique' where the nested loops can be converted to a single
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loop to reduce time complexity.
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"""
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from typing import List
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def max_sum_in_array(array: List[int], k: int) -> int:
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"""
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Returns the maximum sum of k consecutive elements
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>>> arr = [1, 4, 2, 10, 2, 3, 1, 0, 20]
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>>> k = 4
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>>> max_sum_in_array(arr, k)
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24
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>>> k = 10
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>>> max_sum_in_array(arr,k)
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Traceback (most recent call last):
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...
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ValueError: Invalid Input
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>>> arr = [1, 4, 2, 10, 2, 13, 1, 0, 2]
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>>> k = 4
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>>> max_sum_in_array(arr, k)
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27
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"""
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if len(array) < k or k < 0:
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raise ValueError("Invalid Input")
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max_sum = current_sum = sum(array[:k])
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for i in range(len(array) - k):
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current_sum = current_sum - array[i] + array[i + k]
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max_sum = max(max_sum, current_sum)
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return max_sum
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if __name__ == "__main__":
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from doctest import testmod
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from random import randint
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testmod()
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array = [randint(-1000, 1000) for i in range(100)]
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k = randint(0, 110)
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print(f"The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}")
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@ -1,89 +1,89 @@
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"""
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Given an array of integers and another integer target,
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we are required to find a triplet from the array such that it's sum is equal to
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the target.
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"""
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from __future__ import annotations
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from itertools import permutations
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from random import randint
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from timeit import repeat
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def make_dataset() -> tuple[list[int], int]:
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arr = [randint(-1000, 1000) for i in range(10)]
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r = randint(-5000, 5000)
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return (arr, r)
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dataset = make_dataset()
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def triplet_sum1(arr: list[int], target: int) -> tuple[int, int, int]:
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"""
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Returns a triplet in the array with sum equal to target,
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else (0, 0, 0).
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>>> triplet_sum1([13, 29, 7, 23, 5], 35)
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(5, 7, 23)
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>>> triplet_sum1([37, 9, 19, 50, 44], 65)
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(9, 19, 37)
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>>> arr = [6, 47, 27, 1, 15]
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>>> target = 11
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>>> triplet_sum1(arr, target)
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(0, 0, 0)
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"""
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for triplet in permutations(arr, 3):
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if sum(triplet) == target:
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return tuple(sorted(triplet))
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return (0, 0, 0)
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def triplet_sum2(arr: list[int], target: int) -> tuple[int, int, int]:
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"""
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Returns a triplet in the array with sum equal to target,
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else (0, 0, 0).
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>>> triplet_sum2([13, 29, 7, 23, 5], 35)
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(5, 7, 23)
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>>> triplet_sum2([37, 9, 19, 50, 44], 65)
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(9, 19, 37)
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>>> arr = [6, 47, 27, 1, 15]
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>>> target = 11
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>>> triplet_sum2(arr, target)
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(0, 0, 0)
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"""
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arr.sort()
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n = len(arr)
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for i in range(n - 1):
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left, right = i + 1, n - 1
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while left < right:
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if arr[i] + arr[left] + arr[right] == target:
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return (arr[i], arr[left], arr[right])
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elif arr[i] + arr[left] + arr[right] < target:
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left += 1
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elif arr[i] + arr[left] + arr[right] > target:
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right -= 1
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return (0, 0, 0)
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def solution_times() -> tuple[float, float]:
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setup_code = """
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from __main__ import dataset, triplet_sum1, triplet_sum2
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"""
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test_code1 = """
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triplet_sum1(*dataset)
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"""
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test_code2 = """
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triplet_sum2(*dataset)
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"""
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times1 = repeat(setup=setup_code, stmt=test_code1, repeat=5, number=10000)
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times2 = repeat(setup=setup_code, stmt=test_code2, repeat=5, number=10000)
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return (min(times1), min(times2))
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if __name__ == "__main__":
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from doctest import testmod
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testmod()
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times = solution_times()
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print(f"The time for naive implementation is {times[0]}.")
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print(f"The time for optimized implementation is {times[1]}.")
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"""
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Given an array of integers and another integer target,
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we are required to find a triplet from the array such that it's sum is equal to
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the target.
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"""
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from __future__ import annotations
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from itertools import permutations
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from random import randint
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from timeit import repeat
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def make_dataset() -> tuple[list[int], int]:
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arr = [randint(-1000, 1000) for i in range(10)]
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r = randint(-5000, 5000)
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return (arr, r)
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dataset = make_dataset()
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def triplet_sum1(arr: list[int], target: int) -> tuple[int, int, int]:
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"""
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Returns a triplet in the array with sum equal to target,
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else (0, 0, 0).
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>>> triplet_sum1([13, 29, 7, 23, 5], 35)
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(5, 7, 23)
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>>> triplet_sum1([37, 9, 19, 50, 44], 65)
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(9, 19, 37)
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>>> arr = [6, 47, 27, 1, 15]
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>>> target = 11
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>>> triplet_sum1(arr, target)
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(0, 0, 0)
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"""
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for triplet in permutations(arr, 3):
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if sum(triplet) == target:
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return tuple(sorted(triplet))
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return (0, 0, 0)
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def triplet_sum2(arr: list[int], target: int) -> tuple[int, int, int]:
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"""
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Returns a triplet in the array with sum equal to target,
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else (0, 0, 0).
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>>> triplet_sum2([13, 29, 7, 23, 5], 35)
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(5, 7, 23)
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>>> triplet_sum2([37, 9, 19, 50, 44], 65)
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(9, 19, 37)
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>>> arr = [6, 47, 27, 1, 15]
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>>> target = 11
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>>> triplet_sum2(arr, target)
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(0, 0, 0)
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"""
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arr.sort()
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n = len(arr)
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for i in range(n - 1):
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left, right = i + 1, n - 1
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while left < right:
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if arr[i] + arr[left] + arr[right] == target:
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return (arr[i], arr[left], arr[right])
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elif arr[i] + arr[left] + arr[right] < target:
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left += 1
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elif arr[i] + arr[left] + arr[right] > target:
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right -= 1
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return (0, 0, 0)
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def solution_times() -> tuple[float, float]:
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setup_code = """
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from __main__ import dataset, triplet_sum1, triplet_sum2
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"""
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test_code1 = """
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triplet_sum1(*dataset)
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"""
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test_code2 = """
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triplet_sum2(*dataset)
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"""
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times1 = repeat(setup=setup_code, stmt=test_code1, repeat=5, number=10000)
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times2 = repeat(setup=setup_code, stmt=test_code2, repeat=5, number=10000)
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return (min(times1), min(times2))
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if __name__ == "__main__":
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from doctest import testmod
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testmod()
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times = solution_times()
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print(f"The time for naive implementation is {times[0]}.")
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print(f"The time for optimized implementation is {times[1]}.")
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