Merge pull request #6 from theforestvn88/july

July

Author: theforestvn88

0101-0200/0163_missing_ranges.rb

@@ -0,0 +1,25 @@
+# @param {Integer[]} nums
+# @param {Integer} lower
+# @param {Integer} upper
+# @return {Integer[][]}
+def missing_ranges(nums, lower, upper)
+ return [[lower, upper]] if nums.empty?
+
+ ans = []
+
+ if nums[0] > lower
+ ans << [lower, nums[0]-1]
+ end
+
+ nums.each_cons(2) { |a, b|
+ if a < b-1
+ ans << [a+1, b-1]
+ end
+ }
+
+ if nums[-1] < upper
+ ans << [nums[-1]+1, upper]
+ end
+
+ ans
+end

1101-1200/1105_filling_bookcase_shelves.rb

@@ -0,0 +1,28 @@
+# @param {Integer[][]} books
+# @param {Integer} shelf_width
+# @return {Integer}
+def min_height_shelves(books, shelf_width)
+ # defining dp[i] as the min height for placing i books (IN ORDER)
+ dp = Array.new(books.size + 1, Float::INFINITY)
+ dp[0] = 0
+ (0...books.size).each { |i|
+ # for the next i-th book
+ w, h = books[i]
+ # we can:
+ # place it on another level
+ dp[i+1] = dp[i] + h
+ # collect books [j..i-1] and place them at the same level, 0 <= j < i
+ (i-1).downto(0) { |j|
+ w += books[j][0]
+ # Note that we need to place books IN ORDER
+ # so we cannot place the i-th book at the same level of books [j..i-2] which above the (i-1)th book
+ # therefor, if the width of books [j..i] is out of the shelf width, we stop
+ break if w > shelf_width
+
+ h = [h, books[j][1]].max
+ dp[i+1] = [dp[i+1], dp[j] + h].min
+ }
+ }
+
+ dp[books.size]
+end

1301-1400/1395_count_number_of_teams.rb

@@ -0,0 +1,57 @@
+# @param {Integer[]} rating
+# @return {Integer}
+def num_teams(rating)
+ max = rating.max
+ count = 0
+
+ # for each k, there're teams formed by rating[k], previous rating[j] <= rating[k] - 1, and previous ratings[i] < rating[j]
+ # ........ rating[k]-1 rating[k]
+ # [i] j k
+ counter = BinaryIndexedTree.new(max)
+ accumulate = BinaryIndexedTree.new(max)
+ (0...rating.size).each { |k|
+ rate = rating[k]
+ count += accumulate.range_sum(rate-1)
+ accumulate.update(rate, counter.range_sum(rate-1))
+ counter.update(rate, 1)
+ }
+
+ # same as above, but in reverse direction
+ counter = BinaryIndexedTree.new(max)
+ accumulate = BinaryIndexedTree.new(max)
+ (rating.size-1).downto(0) { |k|
+ rate = rating[k]
+ count += accumulate.range_sum(rate-1)
+ accumulate.update(rate, counter.range_sum(rate-1))
+ counter.update(rate, 1)
+ }
+
+ count
+end
+
+class BinaryIndexedTree
+ attr_reader :counter
+
+ def initialize(size)
+ @size = size
+ @counter = Array.new(size+1, 0)
+ end
+
+ def update(index, val)
+ i = index + 1
+ while i <= @size
+ @counter[i] += val
+ i += i & (-i)
+ end
+ end
+
+ def range_sum(index)
+ sum = 0 
+ i = index + 1
+ while i > 0
+ sum += @counter[i]
+ i -= i & (-i)
+ end
+ sum
+ end
+end

1401-1500/1486_xor_operation_in_an_array.rb

@@ -0,0 +1,6 @@
+# @param {Integer} n
+# @param {Integer} start
+# @return {Integer}
+def xor_operation(n, start)
+ n.times.reduce(0) { |acc, i| acc ^= (start + 2*i) }
+end

1501-1600/1566_detect_pattern_of_length_m_repeated_k_or_more_times.rb

@@ -0,0 +1,13 @@
+# @param {Integer[]} arr
+# @param {Integer} m
+# @param {Integer} k
+# @return {Boolean}
+def contains_pattern(arr, m, k)
+ (0..arr.length-m).each { |i|
+ pattern = arr[i...i+m]
+ return true if (k-1).times.all? { |j|
+ pattern == arr[(i + (j+1)*m)...(i + (j+2)*m)]
+ }
+ }
+ false
+end

1601-1700/1653_minimum_deletions_to_make_string_balanced.rb

@@ -0,0 +1,27 @@
+# @param {String} s
+# @return {Integer}
+def minimum_deletions(s)
+ # at the index i
+ # ...........(a|b)...
+ # [ balanced ]
+ # assume that [0..i-1] is balanced by removing some 'a'/'b'
+ # there're 3 ways to make [0..i] is also balanced:
+ # - [1] if 'a' at i then: 
+ # + [1.1] we remove some 'a'/'b' same as [0..i-1] above and remove the 'a' at i
+ # + [1.2] remove all 'b', let 'a' only
+ # - [2] if 'b' at i, we remove some 'a'/'b' same as [0..i-1] above, and keep 'b' at i
+ #
+
+ ans = 0 # number of removing some 'a'/'b' so far
+ b_count = 0 # number of prefix 'b' so far
+ s.each_char { |c|
+ if c == 'b'
+ b_count += 1
+ # case [2], keep b, the ans so far is still optimal
+ else
+ # min of case [1.1] and case [1.2]
+ ans = [ans + 1, b_count].min
+ end
+ }
+ ans
+end

1701-1800/1765_map_of_highest_peak.rb

@@ -0,0 +1,32 @@
+# @param {Integer[][]} is_water
+# @return {Integer[][]}
+def highest_peak(is_water)
+ r = is_water.size
+ c = is_water[0].size
+ result = Array.new(r) { Array.new(c, Float::INFINITY) }
+ 
+ queue = []
+ (0...r).each { |i|
+ (0...c).each { |j|
+ if is_water[i][j] == 1
+ result[i][j] = 0
+ queue << [i, j]
+ end
+ }
+ }
+
+ directions = [[-1, 0], [1, 0], [0, -1], [0, 1]]
+ until queue.empty?
+ i, j = queue.shift
+ directions.each { |dr, dc|
+ _i = i + dr
+ _j = j + dc
+ next if _i < 0 || _i >= r || _j < 0 || _j >= c
+
+ queue << [_i, _j] if result[_i][_j] == Float::INFINITY
+ result[_i][_j] = [result[_i][_j], result[i][j] + 1].min
+ }
+ end
+
+ result
+end

2001-2100/2045_second_minimum_time_to_reach_destination.rb

@@ -0,0 +1,86 @@
+# @param {Integer} n
+# @param {Integer[][]} edges
+# @param {Integer} time
+# @param {Integer} change
+# @return {Integer}
+def second_minimum(n, edges, time, change)
+ adj = Hash.new { |h, k| h[k] = [] }
+ edges.each { |u, v|
+ adj[u] << v
+ adj[v] << u
+ }
+ 
+ costs = Array.new(n+1) { [nil, nil] }
+ queue = MinHeap.new
+ queue.add([0, 1])
+ until queue.empty?
+ t, u = queue.extract_min
+ wait = (t/change).odd? ? change - (t % change) : 0
+ next_t = t + wait + time
+
+ adj[u].each { |v|
+ next if costs[v][1] # already reached 2 times, no need to process
+ 
+ if costs[v][0].nil? # reach the first time
+ costs[v][0] = next_t 
+ else # reach the second time
+ costs[v][1] = next_t if costs[v][1].nil? && costs[v][0] < next_t
+ end
+
+ return costs[v][1] if v == n && costs[v][1]
+
+ queue.add([next_t, v])
+ }
+ end 
+end
+
+class MinHeap
+ def initialize
+ @items = []
+ end
+
+ def add(x)
+ @items.push(x)
+ swim_up(@items.size-1)
+ end
+
+ def extract_min
+ return if empty?
+
+ swap(0, @items.size-1)
+ min = @items.pop()
+ sink_down(0)
+ min
+ end
+
+ def empty?
+ @items.empty?
+ end
+
+ private
+
+ def swap(i, j)
+ temp = @items[i]
+ @items[i] = @items[j]
+ @items[j] = temp
+ end
+
+ def sink_down(i)
+ return if (l = 2*i + 1) >= @items.size
+ r = l + 1
+
+ min = (@items[l] <=> @items[r] || 0) <= 0 ? l : r
+ if (@items[min] <=> @items[i]) < 0
+ swap(min, i)
+ sink_down(min)
+ end
+ end
+
+ def swim_up(i)
+ return if (p = (i-1)/2) < 0
+ if (@items[i] <=> @items[p]) < 0
+ swap(i, p)
+ swim_up(p)
+ end
+ end
+end

2601-2700/2670_find_the_distinct_difference_array.rb

@@ -0,0 +1,19 @@
+# @param {Integer[]} nums
+# @return {Integer[]}
+def distinct_difference_array(nums)
+ prefix_diff = []
+ prefix_appear = Hash.new(false)
+ (0...nums.size).each { |i|
+ prefix_appear[nums[i]] = true
+ prefix_diff[i] = prefix_appear.size
+ }
+
+ suffix_diff = []
+ suffix_appear = Hash.new(false)
+ (nums.size-1).downto(0).map { |i|
+ suffix_diff[i] = suffix_appear.size
+ suffix_appear[nums[i]] = true
+ }
+
+ (0...nums.size).map { |i| prefix_diff[i] - suffix_diff[i] }
+end

3101-3200/3123_find_edges_in_shortest_paths.rb

@@ -0,0 +1,93 @@
+# @param {Integer} n
+# @param {Integer[][]} edges
+# @return {Boolean[]}
+def find_answer(n, edges)
+ adj = Hash.new { |h, k| h[k] = [] }
+ edges.each { |u, v, w|
+ adj[u] << [v, w]
+ adj[v] << [u, w]
+ }
+
+ min_cost_from_source = dijkstra(adj, n, 0)
+ min_cost_from_target = dijkstra(adj, n, n-1)
+
+ edges.map { |u, v, w|
+ min_cost_from_source[n-1] < Float::INFINITY &&
+ (min_cost_from_source[u] + w + min_cost_from_target[v] == min_cost_from_source[n-1] ||
+ min_cost_from_source[v] + w + min_cost_from_target[u] == min_cost_from_source[n-1])
+ }
+end
+
+# https://en.wikipedia.org/wiki/Dijkstra's_algorithm
+def dijkstra(graph, n, source)
+ dist = Array.new(n, Float::INFINITY)
+ dist[source] = 0
+
+ queue = MinHeap.new
+ queue.add([0, source])
+ until queue.empty?
+ cost, v = queue.extract_min
+ next if cost > dist[v]
+ 
+ graph[v].each { |u, w|
+ alt = dist[v] + w
+ if dist[u] > alt
+ dist[u] = alt
+ queue.add([alt, u])
+ end
+ }
+ end
+
+ dist
+end
+
+class MinHeap
+ def initialize
+ @items = []
+ end
+
+ def add(x)
+ @items.push(x)
+ swim_up(@items.size-1)
+ end
+
+ def extract_min
+ return if empty?
+
+ swap(0, @items.size-1)
+ min = @items.pop()
+ sink_down(0)
+ min
+ end
+
+ def empty?
+ @items.empty?
+ end
+
+ private
+
+ def swap(i, j)
+ temp = @items[i]
+ @items[i] = @items[j]
+ @items[j] = temp
+ end
+
+ def sink_down(i)
+ return if (l = 2*i + 1) >= @items.size
+ r = l + 1
+
+ min = (@items[l] <=> @items[r] || 0) <= 0 ? l : r
+ if (@items[min] <=> @items[i]) < 0
+ swap(min, i)
+ sink_down(min)
+ end
+ end
+
+ def swim_up(i)
+ return if (p = (i-1)/2) < 0
+ if (@items[i] <=> @items[p]) < 0
+ swap(i, p)
+ swim_up(p)
+ end
+ end
+end