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https://github.com/TheAlgorithms/C-Plus-Plus.git
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clang-format and clang-tidy fixes for 02439b57
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@@ -26,7 +26,7 @@ class Matrix {
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template <typename Integer,
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typename = typename std::enable_if<
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std::is_integral<Integer>::value, Integer>::type>
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Matrix(const Integer size) {
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explicit Matrix(const Integer size) {
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for (size_t i = 0; i < size; ++i) {
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_mat.emplace_back(std::vector<T>(size, 0));
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}
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@@ -1,21 +1,23 @@
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/**
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* @file sparse_table.cpp
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* @brief Implementation of [Sparse Table](https://en.wikipedia.org/wiki/Range_minimum_query) data structure
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* @brief Implementation of [Sparse
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* Table](https://en.wikipedia.org/wiki/Range_minimum_query) data structure
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*
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* @details
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* Sparse Table is a data structure, that allows answering range queries.
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* It can answer most range queries in O(logn), but its true power is answering range minimum queries
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* or equivalent range maximum queries). For those queries it can compute the answer in O(1) time.
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* It can answer most range queries in O(logn), but its true power is answering
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* range minimum queries or equivalent range maximum queries). For those queries
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* it can compute the answer in O(1) time.
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*
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* * Running Time Complexity \n
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* * Build : O(NlogN) \n
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* * Range Query : O(1) \n
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*/
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*/
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#include <vector>
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#include <algorithm>
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#include <cassert>
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#include <iostream>
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#include <algorithm>
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#include <vector>
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/**
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* @namespace range_queries
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@@ -26,19 +28,19 @@ namespace range_queries {
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* @namespace sparse_table
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* @brief Range queries using sparse-tables
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*/
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namespace sparse_table {
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namespace sparse_table {
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/**
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* This function precomputes intial log table for further use.
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* @param n value of the size of the input array
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* @return corresponding vector of the log table
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*/
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template<typename T>
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template <typename T>
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std::vector<T> computeLogs(const std::vector<T>& A) {
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int n = A.size();
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std::vector<T> logs(n);
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logs[1] = 0;
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for (int i = 2 ; i < n ; i++) {
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logs[i] = logs[i/2] + 1;
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for (int i = 2; i < n; i++) {
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logs[i] = logs[i / 2] + 1;
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}
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return logs;
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}
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@@ -50,19 +52,20 @@ std::vector<T> computeLogs(const std::vector<T>& A) {
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* @param logs array of the log table
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* @return created sparse table data structure
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*/
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template<typename T>
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std::vector<std::vector<T> > buildTable(const std::vector<T>& A, const std::vector<T>& logs) {
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template <typename T>
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std::vector<std::vector<T> > buildTable(const std::vector<T>& A,
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const std::vector<T>& logs) {
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int n = A.size();
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std::vector<std::vector<T> > table(20, std::vector<T>(n+5, 0));
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std::vector<std::vector<T> > table(20, std::vector<T>(n + 5, 0));
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int curLen = 0;
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for (int i = 0 ; i <= logs[n] ; i++) {
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for (int i = 0; i <= logs[n]; i++) {
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curLen = 1 << i;
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for (int j = 0 ; j + curLen < n ; j++) {
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for (int j = 0; j + curLen < n; j++) {
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if (curLen == 1) {
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table[i][j] = A[j];
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}
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else {
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table[i][j] = std::min(table[i-1][j], table[i-1][j + curLen/2]);
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} else {
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table[i][j] =
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std::min(table[i - 1][j], table[i - 1][j + curLen / 2]);
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}
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}
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}
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@@ -77,14 +80,15 @@ std::vector<std::vector<T> > buildTable(const std::vector<T>& A, const std::vect
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* @param table sparse table data structure for the input array
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* @return minimum value for the [beg, end] range for the input array
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*/
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template<typename T>
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int getMinimum(int beg, int end, const std::vector<T>& logs, const std::vector<std::vector<T> >& table) {
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template <typename T>
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int getMinimum(int beg, int end, const std::vector<T>& logs,
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const std::vector<std::vector<T> >& table) {
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int p = logs[end - beg + 1];
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int pLen = 1 << p;
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return std::min(table[p][beg], table[p][end - pLen + 1]);
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}
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}
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} // namespace range_queries
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} // namespace sparse_table
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} // namespace range_queries
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/**
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* Main function
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@@ -92,10 +96,10 @@ int getMinimum(int beg, int end, const std::vector<T>& logs, const std::vector<s
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int main() {
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std::vector<int> A{1, 2, 0, 3, 9};
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std::vector<int> logs = range_queries::sparse_table::computeLogs(A);
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std::vector<std::vector<int> > table = range_queries::sparse_table::buildTable(A, logs);
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std::vector<std::vector<int> > table =
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range_queries::sparse_table::buildTable(A, logs);
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assert(range_queries::sparse_table::getMinimum(0, 0, logs, table) == 1);
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assert(range_queries::sparse_table::getMinimum(0, 4, logs, table) == 0);
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assert(range_queries::sparse_table::getMinimum(2, 4, logs, table) == 0);
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return 0;
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}
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