[!info] Container Adaptor
Stack and queue are not containers, they are container adapters, which can be implemented with different kinds of containers. They don't provide iterators.
232 Implement Queue using Stacks
class MyQueue {
public:
MyQueue() {
}
void push(int x) {
stIn.push(x);
}
int pop() {
move();
int top = stOut.top();
stOut.pop();
return top;
}
int peek() {
move();
return stOut.top();
}
bool empty() {
return stIn.empty() && stOut.empty();
}
private:
void move()
{
if(stOut.empty())
{
while(stIn.size())
{
stOut.push(stIn.top());
stIn.pop();
}
}
}
private:
stack<int> stIn;
stack<int> stOut;
};
225 Implement Stack using Queues
class MyStack {
public:
MyStack() {
}
void push(int x) {
que.push(x);
}
int pop() {
int size = que.size();
while(size > 1)
{
que.push(que.front());
que.pop();
--size;
}
int top = que.front();
que.pop();
return top;
}
int top() {
return que.back();
}
bool empty() {
return que.empty();
}
private:
queue<int> que;
};
20 Valid Parentheses
Given a string s containing just the characters '(', ')', '{', '}', '[' and ']', determine if the input string is valid.
bool isValid(string s) {
stack<char> st;
unordered_map<char, char> pairs =
{
{')', '('},
{']', '['},
{'}', '{'}
};
for(const char& c : s)
{
if(c == '(' || c == '[' || c == '{')
{
st.push(c);
}
else if(!st.empty())
{
auto iter = pairs.find(c);
if(iter == pairs.end() || iter->second != st.top())
return false;
st.pop();
}
else
return false;
}
return st.empty();
}`
1047 Remove all adjacent duplicates in string
A duplicate removal consists of choosing two adjacent and equal letters and removing them.
We repeatedly make duplicate removals on s until we no longer can.
Example 1
s = "abbaca"
output = "ca"
Example 2
s = "abbbaca"
output = "abaca"
string removeDuplicates(string s) {
stack<char> st;
for(const char& c : s)
{
if(!st.empty() && st.top() == c)
{
st.pop();
}
else
{
st.push(c);
}
}
string res(st.size(), 0);
for(int i = st.size() - 1; i >= 0; --i)
{
res[i] = st.top();
st.pop();
}
return res;
}
150 Evaluate Reverse Polish Notation
The operator precedes the two operands.
Example 2:
Input: tokens = ["4","13","5","/","+"]
Output: 6
Explanation: (4 + (13 / 5)) = 6
Example 3:
Input: tokens = ["10","6","9","3","+","-11","","/","","17","+","5","+"]
Output: 22
Explanation: ((10 * (6 / ((9 + 3) * -11))) + 17) + 5
= ((10 * (6 / (12 * -11))) + 17) + 5
int evalRPN(vector<string>& tokens) {
stack<long long> st;
for(const string& s : tokens)
{
// every time encounters a operator
if(s == "+" || s == "-" || s == "*" || s == "/")
{
// pop out the two operands
// be careful about the first retrieved value should be dividend
// so the first poped one should be operand2
long long operand2 = st.top();
st.pop();
long long operand1 = st.top();
st.pop();
// evaluation:
long long res = 0;
char operation = s[0];
switch(operation)
{
case '+':
res = operand1 + operand2;
break;
case '-':
res = operand1 - operand2;
break;
case '*':
res = operand1 * operand2;
break;
case '/':
res = operand1 / operand2;
break;
}
// push result back for further calculatoin
st.push(res);
}
else
{
// stoll: string to long long
// stoi: string to int
st.push(stoll(s));
}
}
return st.top();
}
Sliding Window
239 Sliding Window Maximum
You are given an array of integers nums, there is a sliding window of size k which is moving from the very left of the array to the very right. You can only see the k numbers in the window. Each time the sliding window moves right by one position.
Return the max sliding window.
[!info] Monotonic queue
We don't need record every number in the window, we just need to keep a monotonic decreasing queue, the biggest number is always at the front. It works as:
- the window moves right and
popout a number from front:
- if the popped number == the maximum in the window before, due to it's a monotonic decreasing array, the new front of the queue is the new maximum in the window before insertion of new value.
- if the popped number != max before sliding, that means the max should not be popped out yet, the original max is still the max before insertion
- Either way, we are pretty sure that the
front()is the max after popping before inserting.- sliding windows
pusha new number to the back of the queue:
- keep
pop_back()until theback()is>=the new numberpush(newNumber)>[!important]multisetcan work as a monotonic queue >Since: >- wheninsert, it sorts automatically >- It allows duplicates as we need >- whenerase(find(toBeErasedValue)), it sorts automatically >- we can easily retrieve smallest numberrbegin()or smallest numberbegin()
Monotonic Queue implemented by deque
class MonotonicQueue
{
public:
// implemented by deque, we assign front as pop end
// back as insertion end
deque<int> que;
// --------------
// front <- ..|..|..|.. <- back
// --------------
// pop from the front
// since we are not recording every value in the window
// we only pop when the value == front()
void pop(int value) {
if (!que.empty() && value == que.front()) {
que.pop_front();
}
}
// insert to the back
// keeps poping out back elements until
// the back value is greater than new value, then we push the new value
// this way, we make sure it's monotonic
void push(int value) {
while (!que.empty() && value > que.back()) {
que.pop_back();
}
que.push_back(value);
}
int front() {
return que.front();
}
};
vector<int> maxSlidingWindowByMyMonotonicQueue(vector<int>& nums, int k) {
vector<int> res;
MonotonicQueue que;
for(int i = 0; i < nums.size(); ++i)
{
// before i reaches k, sliding window is not full
// should not pop yet
if(i >= k)
que.pop(nums[i - k]);
// either windows is growing to size k
// or move right
// push either way
que.push(nums[i]);
// when window is full, starts output maximum
if(i >= k - 1)
{
res.emplace_back(que.front());
}
}
return res;
}
multiset as a monotonic queue
Since multiset just sorts automatically, we *insert every number in the sliding window to i*t. To achieve pop(), we find(toBeErasedValue) exactly where the number should be popped at, and erase(itr).
vector<int> maxSlidingWindow(vector<int>& nums, int k) {
multiset<int> monotonicQueue;
vector<int> res;
for(int i = 0; i < nums.size(); ++i)
{
if(i >= k)
monotonicQueue.erase(st.find(nums[i - k]));
monotonicQueue.insert(nums[i]);
if(i >= k - 1)
res.emplace_back(monotonicQueue.rbegin());
}
return res;
}
heap
Compare function for priority_queue
[!caution]
From the above source code, we can see, the compare func in heap is to check whether there should be a swap. So if it returns true, it means fails to meet condition, go swapping, so:
- max-heap: should be passed with compare func that returns true if
lhs < rhs- min-heap: should be passed with compare func that returns true if
lhs > rhsHowever, this is opposite for
std::sort, if the compare function returns true, it means the order oflhsandrhsis correct, no need for swaption.
347 Top k frequent elements
Given an integer array nums and an integer k, return the k most frequent elements. You may return the answer in any order.
// we wanna min-heap, so pass greater comparation
class compareFrequencyPairs
{
public:
bool operator()(const pair<int, int> & lhs, const pair<int, int> & rhs)
{
return lhs.second > rhs.second;
}
};
vector<int> topKFrequent(vector<int>& nums, int k) {
unordered_map<int, int> frequencies;
for(const int & i : nums)
{
++frequencies[i];
}
priority_queue<pair<int, int>, vector<pair<int, int>>, compareFrequencyPairs> heap;
for(auto& pair : frequencies)
{
heap.push(pair);
if(heap.size() > k) // pop all the min and left with largest k pairs
heap.pop();
}
vector<int> result(k);
for (int i = k - 1; i >= 0; i--) {
result[i] = heap.top().first;
heap.pop();
}
return result;
}
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