Proto Van Emde Boas Tree | Set 5 | Queries: Minimum, Maximum
Please check previous sets of Proto Van Emde Boas Tree article first. It is highly recommended.
Procedure for finding minimum:
- Base Case: If the size of Proto-VEB is 2 then we will return smallest key present in the cluster if no keys present then we will return -1 as the symbol that no keys are present.
- Recursion:
- We will start recursion over summary until we reach the first true value(In the code, first not nullptr in the summary cluster) which shows that there is a key present in that cluster.
- Now We will find the position of the key in that cluster using again recursively call over a cluster to find the first true value (In the code, first not nullptr in the cluster) in a cluster as we have done above.
- Finally, we will return the index of that key according to cluster number we get from procedure over summary and position we get from the procedure over the cluster in the last step.
See the image below for the basic understanding of the operation:
Observe the light green circles from top to bottom:
See the image below for real Proto – VEB minimum operation:
Follow the instructions in order of numberings.
You can easily get the idea of Maximum from the minimum procedure. See the image below:
Observe the light green circles from top to bottom:
Implementation of the above algorithm:
C++
// C++ implementation of the approach #include <bits/stdc++.h> using namespace std; class Proto_Van_Emde_Boas { public : // Total number of keys int universe_size; // Summary Proto_Van_Emde_Boas* summary; // Clusters array of Proto-VEB pointers vector<Proto_Van_Emde_Boas*> clusters; int root( int u) { return ( int ) sqrt (u); } // Function to return cluster numbers // in which key is present int high( int x) { return x / root(universe_size); } // Function to return position of x in cluster int low( int x) { return x % root(universe_size); } // Function to return the index from // cluster number and position int generate_index( int cluster, int position) { return cluster * root(universe_size) + position; } // Constructor Proto_Van_Emde_Boas( int size) { universe_size = size; // Base case if (size <= 2) { // Set summary to nullptr as there is no // more summary for size 2 summary = nullptr; // Vector of two pointers // nullptr in starting clusters = vector<Proto_Van_Emde_Boas*>(size, nullptr); } else { // Assigning Proto-VEB(sqrt(u)) to summary summary = new Proto_Van_Emde_Boas(root(size)); // Creating array of Proto-VEB Tree pointers of size sqrt(u) // first all nullptrs are going to assign clusters = vector<Proto_Van_Emde_Boas*>(root(size), nullptr); // Assigning Proto-VEB(sqrt(u)) to all its clusters for ( int i = 0; i < root(size); i++) { clusters[i] = new Proto_Van_Emde_Boas(root(size)); } } } }; // Function that returns true if the // key is present in the tree bool isMember(Proto_Van_Emde_Boas* helper, int key) { // If key is greater then universe_size then // returns false if (key >= helper->universe_size) return false ; // If we reach at base case // the just return whether // pointer is nullptr then false // else return true if (helper->universe_size == 2) { return helper->clusters[key]; } else { // Recursively go deep into the // level of Proto-VEB tree using its // cluster index and its position return isMember(helper->clusters[helper->high(key)], helper->low(key)); } } // Function to insert a key in the tree void insert(Proto_Van_Emde_Boas*& helper, int key) { // If we reach at base case // then assign Proto-VEB(1) in place // of nullptr if (helper->universe_size == 2) { helper->clusters[key] = new Proto_Van_Emde_Boas(1); } else { // Recursively using index of cluster and its // position in cluster insert(helper->clusters[helper->high(key)], helper->low(key)); // Also do the same recursion in summary VEB insert(helper->summary, helper->high(key)); } } // Function to return the minimum key from the tree int minimum(Proto_Van_Emde_Boas* helper) { // Base case choses the least key // present in the cluster if (helper->universe_size == 2) { if (helper->clusters[0]) { return 0; } else if (helper->clusters[1]) { return 1; } // No keys present then return -1 return -1; } else { // Recursively find in summary for // first 1 present in Proto-VEB int minimum_cluster = minimum(helper->summary); int offset; // If no key is present in // the cluster then return -1 if (minimum_cluster == -1) { return -1; } else { // Recursively find the position of the key // in the minimum_cluster offset = minimum(helper->clusters[minimum_cluster]); // Returns overall index of minimum key return helper->generate_index(minimum_cluster, offset); } } } // Function to return the maximum key from the tree int maximum(Proto_Van_Emde_Boas* helper) { // Return the maximum key present in // the cluster if (helper->universe_size == 2) { if (helper->clusters[1]) { return 1; } else if (helper->clusters[0]) { return 0; } // Return -1 if no keys present in the // cluster return -1; } else { // Recursively find the last 1 present // in the summary int maximum_cluster = maximum(helper->summary); int offset; // If no key is present in // the cluster then return -1 if (maximum_cluster == -1) { return -1; } else { // Recursively find the position of the key // in the maximum_cluster offset = maximum(helper->clusters[maximum_cluster]); return helper->generate_index(maximum_cluster, offset); } } } // Function to delete a key from the tree void pveb_delete(Proto_Van_Emde_Boas*& helper, int key) { // Base case: If the key is present // then make it nullptr if (helper->universe_size == 2) { if (helper->clusters[key]) { delete helper->clusters[key]; helper->clusters[key] = nullptr; } } else { // Recursive delete to reach at the base case pveb_delete(helper->clusters[helper->high(key)], helper->low(key)); bool isanyinCluster = false ; // Iterate over the cluster of keys to check whether // any other key is present within that cluster // If yes then we should not update summary to 0 // else update summary to 0 for ( int i = helper->high(key) * helper->root(helper->universe_size); i < (helper->high(key) + 1) * helper->root(helper->universe_size); i++) { // If member is present then break the loop if (isMember(helper->clusters[helper->high(key)], i)) { isanyinCluster = true ; break ; } } // If no member is present then // update summary to zero if (isanyinCluster == false ) { pveb_delete(helper->summary, helper->high(key)); } } } // Driver code int main() { Proto_Van_Emde_Boas* hello = new Proto_Van_Emde_Boas(4); cout << boolalpha; insert(hello, 2); insert(hello, 3); cout << minimum(hello) << endl; cout << maximum(hello) << endl; } |
Java
// Java implementation import java.util.ArrayList; class Proto_Van_Emde_Boas { public int universe_size; public Proto_Van_Emde_Boas summary; // Clusters array of Proto-VEB pointers public ArrayList<Proto_Van_Emde_Boas> clusters; public Proto_Van_Emde_Boas( int size) { universe_size = size; if (size <= 2 ) { summary = null ; clusters = new ArrayList<Proto_Van_Emde_Boas>(size); for ( int i = 0 ; i < size; i++) { clusters.add( null ); } } else { summary = new Proto_Van_Emde_Boas(root(size)); clusters = new ArrayList<Proto_Van_Emde_Boas>( root(size)); for ( int i = 0 ; i < root(size); i++) { clusters.add( new Proto_Van_Emde_Boas(root(size))); } } } public int root( int u) { return ( int )Math.sqrt(u); } // Function to return cluster numbers // in which key is present public int high( int x) { return x / root(universe_size); } // Function to return position of x in cluster public int low( int x) { return x % root(universe_size); } // Function to return the index from // cluster number and position public int generate_index( int cluster, int position) { return cluster * root(universe_size) + position; } } class Main { // Function to insert a key in the tree public static void insert(Proto_Van_Emde_Boas helper, int key) { // If we reach at base case // then assign Proto-VEB(1) in place // of nullptr if (helper.universe_size == 2 ) { helper.clusters.set(key, new Proto_Van_Emde_Boas( 1 )); } else { // Recursively using index of cluster and its // position in cluster insert(helper.clusters.get(helper.high(key)), helper.low(key)); insert(helper.summary, helper.high(key)); } } // Function to return the minimum key from the tree public static int minimum(Proto_Van_Emde_Boas helper) { // Base case choses the least key // present in the cluster if (helper.universe_size == 2 ) { if (helper.clusters.get( 0 ) != null ) { return 0 ; } else if (helper.clusters.get( 1 ) != null ) { return 1 ; } return - 1 ; } else { // Recursively find in summary for // first 1 present in Proto-VEB int minimum_cluster = minimum(helper.summary); int offset; if (minimum_cluster == - 1 ) { // If no key then return -1 return - 1 ; } else { // Recursively find the position of the key // in the minimum_cluster offset = minimum( helper.clusters.get(minimum_cluster)); return helper.generate_index( minimum_cluster, offset); } } } // Function to return the maximum key from the tree public static int maximum(Proto_Van_Emde_Boas helper) { if (helper.universe_size == 2 ) { if (helper.clusters.get( 1 ) != null ) { return 1 ; } else if (helper.clusters.get( 0 ) != null ) { return 0 ; } return - 1 ; // If no key then return -1 } else { // Recursively find in summary for // first 1 present in Proto-VEB int maximum_cluster = maximum(helper.summary); int offset; if (maximum_cluster == - 1 ) { return - 1 ; // If no key then return -1 } else { // Recursively find the position of the key // in the minimum_cluster offset = maximum( helper.clusters.get(maximum_cluster)); return helper.generate_index( maximum_cluster, offset); } } } // Driver code public static void main(String[] args) { Proto_Van_Emde_Boas hello = new Proto_Van_Emde_Boas( 4 ); // inserting insert(hello, 2 ); insert(hello, 3 ); // finding minimun by minimum func. System.out.println(minimum(hello)); // fiding maximum by maximum func. System.out.println(maximum(hello)); } } |
Python3
# Python implementation of the program import math class Proto_Van_Emde_Boas: def __init__( self , size): self .universe_size = size if size < = 2 : self .summary = None self .clusters = [ None ] * size else : self .summary = Proto_Van_Emde_Boas( int (math.sqrt(size))) self .clusters = [Proto_Van_Emde_Boas( int (math.sqrt(size))) for _ in range ( int (math.sqrt(size)))] def root( self , u): return int (math.sqrt(u)) # Function to return cluster numbers # in which key is present def high( self , x): return x / / self .root( self .universe_size) # Function to return position of x in cluster def low( self , x): return x % self .root( self .universe_size) # Function to return the index from # cluster number and position def generate_index( self , cluster, position): return cluster * self .root( self .universe_size) + position # Function to insert a key in the tree def insert(helper, key): if helper.universe_size = = 2 : helper.clusters[key] = Proto_Van_Emde_Boas( 1 ) else : insert(helper.clusters[helper.high(key)], helper.low(key)) insert(helper.summary, helper.high(key)) # Function to find minimum def minimum(helper): if helper.universe_size = = 2 : if helper.clusters[ 0 ] is not None : return 0 elif helper.clusters[ 1 ] is not None : return 1 return - 1 else : minimum_cluster = minimum(helper.summary) if minimum_cluster = = - 1 : return - 1 else : offset = minimum(helper.clusters[minimum_cluster]) return helper.generate_index(minimum_cluster, offset) # Function to find maximum def maximum(helper): if helper.universe_size = = 2 : if helper.clusters[ 1 ] is not None : return 1 elif helper.clusters[ 0 ] is not None : return 0 return - 1 else : maximum_cluster = maximum(helper.summary) if maximum_cluster = = - 1 : return - 1 else : offset = maximum(helper.clusters[maximum_cluster]) return helper.generate_index(maximum_cluster, offset) # Driver code hello = Proto_Van_Emde_Boas( 4 ) # inserting insert(hello, 2 ); insert(hello, 3 ); print (minimum(hello)) print (maximum(hello)) |
Javascript
// JavaScript implementation of the program class Proto_Van_Emde_Boas { constructor(size) { this .universe_size = size; if (size <= 2) { this .summary = null ; this .clusters = new Array(size).fill( null ); } else { this .summary = new Proto_Van_Emde_Boas(Math.sqrt(size)); this .clusters = Array(Math.sqrt(size)).fill().map(() => { return new Proto_Van_Emde_Boas(Math.sqrt(size)); }); } } root(u) { return Math.sqrt(u); } // Function to return cluster numbers // in which key is present high(x) { return Math.floor(x / this .root( this .universe_size)); } // Function to return position of x in cluster low(x) { return x % this .root( this .universe_size); } // Function to return the index from // cluster number and position generate_index(cluster, position) { return cluster * this .root( this .universe_size) + position; } } // Function to insert a key in the tree function insert(helper, key) { if (helper.universe_size == 2) { helper.clusters[key] = new Proto_Van_Emde_Boas(1); } else { insert(helper.clusters[helper.high(key)], helper.low(key)); insert(helper.summary, helper.high(key)); } } // Function to find minimum function minimum(helper) { if (helper.universe_size == 2) { if (helper.clusters[0] !== null ) { return 0; } else if (helper.clusters[1] !== null ) { return 1; } return -1; } else { let minimum_cluster = minimum(helper.summary); if (minimum_cluster == -1) { return -1; } else { let offset = minimum(helper.clusters[minimum_cluster]); return helper.generate_index(minimum_cluster, offset); } } } // Function to find maximum function maximum(helper) { if (helper.universe_size == 2) { if (helper.clusters[1] !== null ) { return 1; } else if (helper.clusters[0] !== null ) { return 0; } return -1; } else { let maximum_cluster = maximum(helper.summary); if (maximum_cluster == -1) { return -1; } else { let offset = maximum(helper.clusters[maximum_cluster]); return helper.generate_index(maximum_cluster, offset); } } } // Driver code let hello = new Proto_Van_Emde_Boas(4); // inserting insert(hello, 2); insert(hello, 3); console.log(minimum(hello)); console.log(maximum(hello)); |
C#
using System; using System.Collections.Generic; public class Proto_Van_Emde_Boas { public int universe_size; public Proto_Van_Emde_Boas summary; public List<Proto_Van_Emde_Boas> clusters; public Proto_Van_Emde_Boas( int size) { universe_size = size; if (size <= 2) { summary = null ; clusters = new List<Proto_Van_Emde_Boas>(size); for ( int i = 0; i < size; i++) { clusters.Add( null ); } } else { summary = new Proto_Van_Emde_Boas(root(size)); clusters = new List<Proto_Van_Emde_Boas>(root(size)); for ( int i = 0; i < root(size); i++) { clusters.Add( new Proto_Van_Emde_Boas(root(size))); } } } public int root( int u) { return ( int )Math.Sqrt(u); } public int high( int x) { return x / root(universe_size); } public int low( int x) { return x % root(universe_size); } public int generate_index( int cluster, int position) { return cluster * root(universe_size) + position; } } public class GFG { public static void insert(Proto_Van_Emde_Boas helper, int key) { if (helper.universe_size == 2) { helper.clusters[key] = new Proto_Van_Emde_Boas(1); } else { insert(helper.clusters[helper.high(key)], helper.low(key)); insert(helper.summary, helper.high(key)); } } public static int minimum(Proto_Van_Emde_Boas helper) { if (helper.universe_size == 2) { if (helper.clusters[0] != null ) { return 0; } else if (helper.clusters[1] != null ) { return 1; } return -1; } else { int minimum_cluster = minimum(helper.summary); int offset; if (minimum_cluster == -1) { return -1; } else { offset = minimum( helper.clusters[minimum_cluster]); return helper.generate_index( minimum_cluster, offset); } } } public static int maximum(Proto_Van_Emde_Boas helper) { if (helper.universe_size == 2) { if (helper.clusters[1] != null ) { return 1; } else if (helper.clusters[0] != null ) { return 0; } return -1; } else { int maximum_cluster = maximum(helper.summary); int offset; if (maximum_cluster == -1) { return -1; } else { offset = maximum( helper.clusters[maximum_cluster]); return helper.generate_index( maximum_cluster, offset); } } } static void Main() { Proto_Van_Emde_Boas hello = new Proto_Van_Emde_Boas(4); insert(hello, 2); insert(hello, 3); Console.WriteLine(minimum(hello)); // fiding maximum by maximum func. Console.WriteLine(maximum(hello)); } } // The code is contributed by Nidhi goel. |
Output
2 3
Both Minimum and Maximum query runs in O(log2(u)) time complexity.
Recurrence Relation:
T(u) = 2T() + O(1)
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