Add two pointer approach

This commit is contained in:
Vitor Oliveira 2021-03-11 21:58:44 -08:00
parent f1cf95fa6e
commit 2b5c1b9d02
2 changed files with 96 additions and 22 deletions

View file

@ -22,6 +22,7 @@ print(sorted_squares([4, -1, -9, 2]))
def bubble_sort(array)
array_length = array.size
return array if array_length <= 1
loop do
swapped = false
(array_length - 1).times do |i|

View file

@ -1,4 +1,5 @@
# Challenge name: Two Sum
#
# Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
#
# You may assume that each input would have exactly one solution, and you may not use the same element twice.
@ -23,44 +24,52 @@
# @param {Integer} target
# @return {Integer[]}
#
#
# Approach 1: Brute Force with Addition
#
# Complexity analysis
# Time Complexity: O(n^2). For each element, we try to find its complement
# by looping through the rest of the array which takes O(n) time.
# Therefore, the time complexity is O(n^2)
# Space complexity: O(1)
#
def two_sum(nums, target)
result_array = []
nums.each_with_index do |num, i|
nums.each_with_index do |num, j|
if i != j && i < j
current_sum = nums[i] + nums[j]
if current_sum == target
return [i, j]
end
end
nums.count.times do |i|
nums.count.times do |j|
next unless i != j && i < j
current_sum = nums[i] + nums[j]
return [i, j] if current_sum == target
end
end
end
print two_sum([2, 7, 11, 15], 9)
print(two_sum([2, 7, 11, 15], 9))
# => [0,1]
print two_sum([3, 2, 4], 6)
print(two_sum([3, 2, 4], 6))
# => [1,2]
print two_sum([3, 3], 6)
print(two_sum([3, 3], 6))
# => [0,1]
#
# Approach 2: Brute Force with Difference
#
# Complexity analysis
#
# Time Complexity: O(N^2), where N is the length of the array
#
def two_sum(nums, target)
nums.each_with_index do |num, i|
nums.count.times do |i|
target_difference = target - nums[i]
nums.each_with_index do |num, j|
if i != j && num == target_difference
return [i, j]
@ -69,38 +78,102 @@ def two_sum(nums, target)
end
end
print two_sum([2, 7, 11, 15], 9)
print(two_sum([2, 7, 11, 15], 9))
# => [0,1]
print two_sum([3, 2, 4], 6)
print(two_sum([3, 2, 4], 6))
# => [1,2]
print two_sum([3, 3], 6)
print(two_sum([3, 3], 6))
# => [0,1]
#
# Approach 3: Using a Hash
#
# Complexity analysis
# Time complexity: O(n). We traverse the list containing n elements exactly twice.
# Since the hash table reduces the lookup time to O(1), the time complexity is O(n).
# Space complexity: O(n). The extra space required depends on the number of items
# stored in the hash table, which stores exactly n elements.
#
def two_sum(nums, target)
hash = {}
# create a hash to store values and their indices
nums.each_with_index do |num, i|
hash[num] = i
end
# iterate over nums array to find the target (difference between sum target and num)
nums.each_with_index do |num, i|
difference_target = target - num
return [i, hash[difference_target]] if hash[difference_target] && hash[difference_target] != i
if hash[difference_target] && hash[difference_target] != i
return [i, hash[difference_target]]
end
end
end
print two_sum([2, 7, 11, 15], 9)
nums = [2, 7, 11, 15]
target = 9
print(two_sum(nums, target))
# => [0,1]
print two_sum([3, 2, 4], 6)
nums = [3, 2, 4]
target = 6
print(two_sum(nums, target))
# => [1,2]
print two_sum([3, 3], 6)
nums = [3, 3]
target = 6
print(two_sum(nums, target))
# => [0,1]
#
# Approach 4: Two pointers
#
# Complexity analysis
# Time complexity: O(n). Each of the n elements is visited at
# most once, thus the time complexity is O(n).
# Space complexity: O(1). We only use two indexes, the space
# complexity is O(1).
def two_sum(numbers, target)
i = 0
j = numbers.length - 1
# note: sorting the array is important
numbers = numbers.sort
while i < j
sum = numbers[i] + numbers[j]
if target < sum
j -= 1
elsif target > sum
i += 1
else
return [i, j]
end
end
end
nums = [2, 7, 11, 15]
target = 9
print(two_sum(nums, target))
# => [0,1]
nums = [2, 3, 4]
target = 6
print(two_sum(nums, target))
# => [0,2]
nums = [-1, 0]
target = -1
print(two_sum(nums, target))
# => [0,1]