From e676e283eaf7170d38f802d12b982a7129598989 Mon Sep 17 00:00:00 2001 From: sidaksohi <31377210+sidaksohi@users.noreply.github.com> Date: Sun, 22 Aug 2021 15:45:08 -0700 Subject: [PATCH] Add array solutions with descriptions --- data_structures/arrays/3sum.rb | 80 +++++++++++++++++++ .../arrays/maximum_product_subarray.rb | 44 ++++++++++ data_structures/arrays/maximum_subarray.rb | 56 +++++++++++++ 3 files changed, 180 insertions(+) create mode 100644 data_structures/arrays/3sum.rb create mode 100644 data_structures/arrays/maximum_product_subarray.rb create mode 100644 data_structures/arrays/maximum_subarray.rb diff --git a/data_structures/arrays/3sum.rb b/data_structures/arrays/3sum.rb new file mode 100644 index 0000000..1e4bf80 --- /dev/null +++ b/data_structures/arrays/3sum.rb @@ -0,0 +1,80 @@ +#Given an integer array nums, return all the triplets [nums[i], nums[j], nums[k]] .. +#.. such that i != j, i != k, and j != k, and nums[i] + nums[j] + nums[k] == 0. +#Notice that the solution set must not contain duplicate triplets. + +#Example 1: +#Input: nums = [-1,0,1,2,-1,-4] +#Output: [[-1,-1,2],[-1,0,1]] + +#Example 2: +#Input: nums = [] +#Output: [] + +#Example 3: +#Input: nums = [0] +#Output: [] + +#Constraints: +#0 <= nums.length <= 3000 +#-105 <= nums[i] <= 105 + + + + +#Two Pointer Approach - O(n) Time / O(1) Space +#Return edge cases. +#Sort nums, and init ans array +#For each |val, index| in nums: +#if the current value is the same as last, then go to next iteration +#init left and right pointers for two pointer search of the two sum in remaining elements of array +#while left < right: +#find current sum +#if sum > 0, right -= 1 +#if sum < 0, left += 1 +#if it's 0, then add the values to the answer array, and set the left pointer to the next valid value .. +#.. (left += 1 while nums[left] == nums[left - 1] && left < right) +#Return ans[] + + +# @param {Integer[]} nums +# @return {Integer[][]} +def three_sum(nums) + #return if length too short + return [] if nums.length < 3 + + #sort nums, init ans array + nums, ans = nums.sort, [] + + #loop through nums + nums.each_with_index do |val, ind| + #if the previous value is the same as current, then skip this iteration as it would create duplicates + next if ind > 0 && nums[ind] == nums[ind - 1] + + #init & run two pointer search + left, right = ind + 1, nums.length - 1 + + while left < right + #find current sum + sum = val + nums[left] + nums[right] + + #decrease sum if it's too great, increase sum if it's too low + if sum > 0 + right -= 1 + elsif sum < 0 + left += 1 + #if it's zero, then add the answer to array and set left pointer to next valid value + else + ans << [val, nums[left], nums[right]] + + left += 1 + + while nums[left] == nums[left - 1] && left < right + left += 1 + end + end + end + end + + #return answer + ans +end \ No newline at end of file diff --git a/data_structures/arrays/maximum_product_subarray.rb b/data_structures/arrays/maximum_product_subarray.rb new file mode 100644 index 0000000..da458bc --- /dev/null +++ b/data_structures/arrays/maximum_product_subarray.rb @@ -0,0 +1,44 @@ +#Given an integer array nums, find a contiguous non-empty subarray within the array that has the largest product, and return the product. +#It is guaranteed that the answer will fit in a 32-bit integer. +#A subarray is a contiguous subsequence of the array. + +#Example 1: +#Input: nums = [2,3,-2,4] +#Output: 6 +#Explanation: [2,3] has the largest product 6. + +#Example 2: +#Input: nums = [-2,0,-1] +#Output: 0 +#Explanation: The result cannot be 2, because [-2,-1] is not a subarray. + +#Constraints: +#1 <= nums.length <= 2 * 104 +#-10 <= nums[i] <= 10 +#The product of any prefix or suffix of nums is guaranteed to fit in a 32-bit integer. + + + + +#Dynamic Programming Approach (Kadane's Algorithm) - O(n) Time / O(1) Space +#Track both current minimum and current maximum (Due to possibility of multiple negative numbers) +#Answer is the highest value of current maximum + + +# @param {Integer[]} nums +# @return {Integer} +def max_product(nums) + return nums[0] if nums.length == 1 + + cur_min, cur_max, max = 1, 1, -11 + + nums.each do |val| + tmp_cur_max = cur_max + cur_max = [val, val*cur_max, val*cur_min].max + cur_min = [val, val*tmp_cur_max, val*cur_min].min + + max = [max, cur_max].max + end + + max +end \ No newline at end of file diff --git a/data_structures/arrays/maximum_subarray.rb b/data_structures/arrays/maximum_subarray.rb new file mode 100644 index 0000000..5c85167 --- /dev/null +++ b/data_structures/arrays/maximum_subarray.rb @@ -0,0 +1,56 @@ +#Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum. +#A subarray is a contiguous part of an array. + +#Example 1: +#Input: nums = [-2,1,-3,4,-1,2,1,-5,4] +#Output: 6 +#Explanation: [4,-1,2,1] has the largest sum = 6. + +#Example 2: +#Input: nums = [1] +#Output: 1 + +#Example 3: +#Input: nums = [5,4,-1,7,8] +#Output: 23 + +#Constraints: +#1 <= nums.length <= 3 * 104 +#-105 <= nums[i] <= 105 + + + + +#Sliding Window Approach - O(n) Time / O(1) Space +#Init max_sum as first element +#Return first element if the array length is 1 +#Init current_sum as 0 +#Iterate through the array: +#if current_sum < 0, then reset it to 0 (to eliminate any negative prefixes) +#current_sum += num +#max_sum = current_sum if current_sum is greater than max_sum +#Return max_sum + + +# @param {Integer[]} nums +# @return {Integer} +def max_sub_array(nums) + #initialize max sum to first number + max_sum = nums[0] + + #return first number if array length is 1 + return max_sum if nums.length == 1 + + #init current sum to 0 + current_sum = 0 + + #iterate through array, reset current_sum to 0 if it ever goes below 0, track max_sum with highest current_sum + nums.each do |num| + current_sum = 0 if current_sum < 0 + current_sum += num + max_sum = [max_sum, current_sum].max + end + + #return answer + max_sum +end \ No newline at end of file