EINFÜHRUNG IN DISJOINT SET (UNION-FIND-ALGORITHMUS)

Was ist eine disjunkte Mengendatenstruktur?

Es werden zwei Mengen aufgerufen disjunkte Mengen Wenn sie kein gemeinsames Element haben, ist der Durchschnitt der Mengen eine Nullmenge.

Eine Datenstruktur, die nicht überlappende oder disjunkte Teilmengen von Elementen speichert, wird als disjunkte Mengendatenstruktur bezeichnet. Die disjunkte Mengendatenstruktur unterstützt folgende Operationen:

Hinzufügen neuer Mengen zur disjunkten Menge.
Disjunkte Mengen zu einer einzigen disjunkten Menge zusammenführen mit Union Betrieb.
Repräsentanten einer disjunkten Menge finden mit Finden Betrieb.
Überprüfen Sie, ob zwei Mengen disjunkt sind oder nicht.

Stellen Sie sich eine Situation mit mehreren Personen und den folgenden Aufgaben vor, die an ihnen ausgeführt werden müssen:

Füge hinzu ein neue Freundschaft Beziehung , d. h. eine Person x wird der Freund einer anderen Person y, d. h. sie fügt einer Menge ein neues Element hinzu.
Finden Sie heraus, ob individuell x ist ein Freund von Person y (direkter oder indirekter Freund)

Beispiele:

Uns werden 10 Personen gegeben, sagen wir: a, b, c, d, e, f, g, h, i, j

Folgende Beziehungen müssen hinzugefügt werden:
ein b
b d
cf
c ich
j e
g j

Bei Fragen wie „a ist ein Freund von d“ oder nicht. Grundsätzlich müssen wir die folgenden vier Gruppen erstellen und eine schnell zugängliche Verbindung zwischen den Gruppenelementen aufrechterhalten:
G1 = {a, b, d}
G2 = {c, f, i}
G3 = {e,g,j}
G4 = {h}

Finden Sie heraus, ob x und y zur selben Gruppe gehören oder nicht, d. h. um herauszufinden, ob x und y direkte/indirekte Freunde sind.

Aufteilung der Individuen in verschiedene Gruppen entsprechend der Gruppe, zu der sie gehören. Diese Methode ist als a bekannt Disjunkte Mengenvereinigung die eine Sammlung von unterhält Disjunkte Mengen und jede Menge wird durch eines ihrer Mitglieder repräsentiert.

Um die obige Frage zu beantworten, sind zwei wichtige Punkte zu berücksichtigen:

Wie löst man Mengen auf? Zunächst gehören alle Elemente zu unterschiedlichen Mengen. Nachdem wir die gegebenen Beziehungen bearbeitet haben, wählen wir ein Mitglied als a aus Vertreter . Es gibt viele Möglichkeiten, einen Vertreter auszuwählen. Eine einfache Möglichkeit besteht darin, mit dem größten Index auszuwählen.
Überprüfen Sie, ob 2 Personen in derselben Gruppe sind? Wenn die Vertreter zweier Personen gleich sind, werden sie Freunde.

Verwendete Datenstrukturen sind:

Array: Ein Array von ganzen Zahlen wird aufgerufen Elternteil[] . Wenn wir uns damit befassen N Elemente, das i-te Element des Arrays stellt das i-te Element dar. Genauer gesagt ist das i-te Element des Parent[]-Arrays das übergeordnete Element des i-ten Elements. Durch diese Beziehungen entstehen ein oder mehrere virtuelle Bäume.

Baum: es ist ein Disjunkte Menge . Wenn sich zwei Elemente im selben Baum befinden, befinden sie sich im selben Baum Disjunkte Menge . Der Wurzelknoten (oder der oberste Knoten) jedes Baums wird als bezeichnet Vertreter des Sets. Es gibt immer eine Single einzigartiger Vertreter jedes Satzes. Eine einfache Regel zur Identifizierung eines Repräsentanten lautet: Wenn „i“ der Repräsentant einer Menge ist, dann Parent[i] = i . Wenn i nicht der Repräsentant seiner Menge ist, kann es gefunden werden, indem man den Baum hinaufgeht, bis wir den Repräsentanten finden.

Operationen an disjunkten Mengendatenstrukturen:

Finden
Union

1. Finden Sie:

Kann durch rekursives Durchlaufen des übergeordneten Arrays implementiert werden, bis wir auf einen Knoten stoßen, der der übergeordnete Knoten von sich selbst ist.

C++

// Finds the representative of the set> // that i is an element of> > #include> using> namespace> std;> > int> find(>int> i)> > {> > >// If i is the parent of itself> >if> (parent[i] == i) {> > >// Then i is the representative of> >// this set> >return> i;> >}> >else> {> > >// Else if i is not the parent of> >// itself, then i is not the> >// representative of his set. So we> >// recursively call Find on its parent> >return> find(parent[i]);> >}> }> > // The code is contributed by Nidhi goel>

Java

// Finds the representative of the set> // that i is an element of> import> java.io.*;> > class> GFG {> > >static> int> find(>int> i)> > >{> > >// If i is the parent of itself> >if> (parent[i] == i) {> > >// Then i is the representative of> >// this set> >return> i;> >}> >else> {> > >// Else if i is not the parent of> >// itself, then i is not the> >// representative of his set. So we> >// recursively call Find on its parent> >return> find(parent[i]);> >}> >}> }> > // The code is contributed by Nidhi goel>

Python3

# Finds the representative of the set> # that i is an element of> > def> find(i):> > ># If i is the parent of itself> >if> (parent[i]>=>=> i):> > ># Then i is the representative of> ># this set> >return> i> >else>:> > ># Else if i is not the parent of> ># itself, then i is not the> ># representative of his set. So we> ># recursively call Find on its parent> >return> find(parent[i])> > ># The code is contributed by Nidhi goel>

C#

using> System;> > public> class> GFG{> > >// Finds the representative of the set> >// that i is an element of> >public> static> int> find(>int> i)> >{> > >// If i is the parent of itself> >if> (parent[i] == i) {> > >// Then i is the representative of> >// this set> >return> i;> >}> >else> {> > >// Else if i is not the parent of> >// itself, then i is not the> >// representative of his set. So we> >// recursively call Find on its parent> >return> find(parent[i]);> >}> >}> }>

Javascript

> // Finds the representative of the set> // that i is an element of> > function> find(i)> {> > >// If i is the parent of itself> >if> (parent[i] == i) {> > >// Then i is the representative of> >// this set> >return> i;> >}> >else> {> > >// Else if i is not the parent of> >// itself, then i is not the> >// representative of his set. So we> >// recursively call Find on its parent> >return> find(parent[i]);> >}> }> // The code is contributed by Nidhi goel> >

Zeitkomplexität : Dieser Ansatz ist ineffizient und kann im schlimmsten Fall O(n) Zeit in Anspruch nehmen.

2. Gewerkschaft:

Es braucht zwei Elemente als Eingabe und findet die Vertreter ihrer Mengen mithilfe von Finden Operation und platziert schließlich einen der Bäume (der die Menge darstellt) unter dem Wurzelknoten des anderen Baums.

C++

// Unites the set that includes i> // and the set that includes j> > #include> using> namespace> std;> > void> union>(>int> i,>int> j) {> > >// Find the representatives> >// (or the root nodes) for the set> >// that includes i> >int> irep =>this>.Find(i),> > >// And do the same for the set> >// that includes j> >int> jrep =>this>.Find(j);> > >// Make the parent of i’s representative> >// be j’s representative effectively> >// moving all of i’s set into j’s set)> >this>.Parent[irep] = jrep;> }>

Java

import> java.util.Arrays;> > public> class> UnionFind {> >private> int>[] parent;> > >public> UnionFind(>int> size) {> >// Initialize the parent array with each element as its own representative> >parent =>new> int>[size];> >for> (>int> i =>0>

; i   parent[i] = i;   }   }     // Find the representative (root) of the set that includes element i   public int find(int i) {   if (parent[i] == i) {   return i; // i is the representative of its own set   }   // Recursively find the representative of the parent until reaching the root   parent[i] = find(parent[i]); // Path compression   return parent[i];   }     // Unite (merge) the set that includes element i and the set that includes element j   public void union(int i, int j) {   int irep = find(i); // Find the representative of set containing i   int jrep = find(j); // Find the representative of set containing j     // Make the representative of i's set be the representative of j's set   parent[irep] = jrep;   }     public static void main(String[] args) {   int size = 5; // Replace with your desired size   UnionFind uf = new UnionFind(size);     // Perform union operations as needed   uf.union(1, 2);   uf.union(3, 4);     // Check if elements are in the same set   boolean inSameSet = uf.find(1) == uf.find(2);   System.out.println('Are 1 and 2 in the same set? ' + inSameSet);   }  }>

Python3

# Unites the set that includes i> # and the set that includes j> > def> union(parent, rank, i, j):> ># Find the representatives> ># (or the root nodes) for the set> ># that includes i> >irep>=> find(parent, i)> > ># And do the same for the set> ># that includes j> >jrep>=> find(parent, j)> > ># Make the parent of i’s representative> ># be j’s representative effectively> ># moving all of i’s set into j’s set)> > >parent[irep]>=> jrep>

C#

using> System;> > public> class> UnionFind> {> >private> int>[] parent;> > >public> UnionFind(>int> size)> >{> >// Initialize the parent array with each element as its own representative> >parent =>new> int>[size];> >for> (>int>

i = 0; i   {   parent[i] = i;   }   }     // Find the representative (root) of the set that includes element i   public int Find(int i)   {   if (parent[i] == i)   {   return i; // i is the representative of its own set   }   // Recursively find the representative of the parent until reaching the root   parent[i] = Find(parent[i]); // Path compression   return parent[i];   }     // Unite (merge) the set that includes element i and the set that includes element j   public void Union(int i, int j)   {   int irep = Find(i); // Find the representative of set containing i   int jrep = Find(j); // Find the representative of set containing j     // Make the representative of i's set be the representative of j's set   parent[irep] = jrep;   }     public static void Main()   {   int size = 5; // Replace with your desired size   UnionFind uf = new UnionFind(size);     // Perform union operations as needed   uf.Union(1, 2);   uf.Union(3, 4);     // Check if elements are in the same set   bool inSameSet = uf.Find(1) == uf.Find(2);   Console.WriteLine('Are 1 and 2 in the same set? ' + inSameSet);   }  }>

Javascript

// JavaScript code for the approach> > // Unites the set that includes i> // and the set that includes j> function> union(parent, rank, i, j)> {> > // Find the representatives> // (or the root nodes) for the set> // that includes i> let irep = find(parent, i);> > // And do the same for the set> // that includes j> let jrep = find(parent, j);> > // Make the parent of i’s representative> // be j’s representative effectively> // moving all of i’s set into j’s set)> > parent[irep] = jrep;> }>

Zeitkomplexität : Dieser Ansatz ist ineffizient und könnte im schlimmsten Fall zu einem Baum der Länge O(n) führen.

Optimierungen (Vereinigung nach Rang/Größe und Pfadkomprimierung):

Die Effizienz hängt stark davon ab, welche Bäume aneinander befestigt werden . Es gibt zwei Möglichkeiten, dies zu tun. Erstens handelt es sich um „Vereinigung nach Rang“, bei der die Höhe des Baums als Faktor berücksichtigt wird, und zweitens um „Vereinigung nach Größe“, bei der die Größe des Baums als Faktor für die Verbindung eines Baums mit dem anderen berücksichtigt wird. Diese Methode sorgt zusammen mit der Pfadkomprimierung für eine Komplexität mit nahezu konstanter Zeit.

Pfadkomprimierung (Änderungen an Find()):

Es beschleunigt die Datenstruktur um Komprimierung der Höhe der Bäume. Dies kann durch Einfügen eines kleinen Caching-Mechanismus in das erreicht werden Finden Betrieb. Schauen Sie sich den Code für weitere Details an:

C++

// Finds the representative of the set that i> // is an element of.> > #include> using> namespace> std;> > int> find(>int> i)> {> > >// If i is the parent of itself> >if> (Parent[i] == i) {> > >// Then i is the representative> >return> i;> >}> >else> {> > >// Recursively find the representative.> >int> result = find(Parent[i]);> > >// We cache the result by moving i’s node> >// directly under the representative of this> >// set> >Parent[i] = result;> > >// And then we return the result> >return> result;> >}> }>

Java

// Finds the representative of the set that i> // is an element of.> import> java.io.*;> import> java.util.*;> > static> int> find(>int> i)> {> > >// If i is the parent of itself> >if> (Parent[i] == i) {> > >// Then i is the representative> >return> i;> >}> >else> {> > >// Recursively find the representative.> >int> result = find(Parent[i]);> > >// We cache the result by moving i’s node> >// directly under the representative of this> >// set> >Parent[i] = result;> > >// And then we return the result> >return> result;> >}> }> > // The code is contributed by Arushi jindal.>

Python3

# Finds the representative of the set that i> # is an element of.> > > def> find(i):> > ># If i is the parent of itself> >if> Parent[i]>=>=> i:> > ># Then i is the representative> >return> i> >else>:> > ># Recursively find the representative.> >result>=> find(Parent[i])> > ># We cache the result by moving i’s node> ># directly under the representative of this> ># set> >Parent[i]>=> result> > ># And then we return the result> >return> result> > # The code is contributed by Arushi Jindal.>

C#

diskrete mathematische Negation

using> System;> > // Finds the representative of the set that i> // is an element of.> public> static> int> find(>int> i)> {> > >// If i is the parent of itself> >if> (Parent[i] == i) {> > >// Then i is the representative> >return> i;> >}> >else> {> > >// Recursively find the representative.> >int> result = find(Parent[i]);> > >// We cache the result by moving i’s node> >// directly under the representative of this> >// set> >Parent[i] = result;> > >// And then we return the result> >return> result;> >}> }> > // The code is contributed by Arushi Jindal.>

Javascript

// Finds the representative of the set that i> // is an element of.> > > function> find(i)> {> > >// If i is the parent of itself> >if> (Parent[i] == i) {> > >// Then i is the representative> >return> i;> >}> >else> {> > >// Recursively find the representative.> >let result = find(Parent[i]);> > >// We cache the result by moving i’s node> >// directly under the representative of this> >// set> >Parent[i] = result;> > >// And then we return the result> >return> result;> >}> }> > // The code is contributed by Arushi Jindal.>

Zeitkomplexität : O(log n) im Durchschnitt pro Anruf.

Union nach Rang :

Zunächst benötigen wir ein neues Array von Ganzzahlen namens Rang[] . Die Größe dieses Arrays entspricht der des übergeordneten Arrays Elternteil[] . Wenn ich ein Vertreter einer Menge bin, Rang[i] ist die Höhe des Baums, der die Menge darstellt.
Denken Sie daran, dass es bei der Union-Operation keine Rolle spielt, welcher der beiden Bäume unter den anderen verschoben wird. Was wir nun tun wollen, ist, die Höhe des resultierenden Baums zu minimieren. Wenn wir zwei Bäume (oder Mengen) vereinen, nennen wir sie links und rechts, dann hängt alles davon ab Rang der Linken und das Rang des Rechts .

Wenn der Rang von links ist kleiner als der Rang von Rechts , dann ist es am besten, umzuziehen links unter rechts , da dies den Rang von rechts nicht ändert (während eine Bewegung nach rechts unter links die Höhe erhöhen würde). Wenn der Rang von rechts kleiner ist als der Rang von links, sollten wir uns auf die gleiche Weise von rechts nach links bewegen.
Wenn die Ränge gleich sind, spielt es keine Rolle, welcher Baum unter dem anderen liegt, aber der Rang des Ergebnisses ist immer um eins größer als der Rang der Bäume.

C++

// Unites the set that includes i and the set> // that includes j by rank> > #include> using> namespace> std;> > void> unionbyrank(>int> i,>int> j) {> > >// Find the representatives (or the root nodes)> >// for the set that includes i> >int> irep =>this>.find(i);> > >// And do the same for the set that includes j> >int> jrep =>this>.Find(j);> > >// Elements are in same set, no need to> >// unite anything.> >if> (irep == jrep)> >return>;> > >// Get the rank of i’s tree> >irank = Rank[irep],> > >// Get the rank of j’s tree> >jrank = Rank[jrep];> > >// If i’s rank is less than j’s rank> >if>

(irank     // Then move i under j   this.parent[irep] = jrep;   }     // Else if j’s rank is less than i’s rank   else if (jrank     // Then move j under i   this.Parent[jrep] = irep;   }     // Else if their ranks are the same   else {     // Then move i under j (doesn’t matter   // which one goes where)   this.Parent[irep] = jrep;     // And increment the result tree’s   // rank by 1   Rank[jrep]++;   }  }>

Java

public> class> DisjointSet {> > >private> int>[] parent;> >private> int>[] rank;> > >// Constructor to initialize the DisjointSet data> >// structure> >public> DisjointSet(>int> size)> >{> >parent =>new> int>[size];> >rank =>new> int>[size];> > >// Initialize each element as a separate set with> >// rank 0> >for> (>int> i =>0>

; i   parent[i] = i;   rank[i] = 0;   }   }     // Function to find the representative (or the root   // node) of a set with path compression   private int find(int i)   {   if (parent[i] != i) {   parent[i] = find(parent[i]); // Path compression   }   return parent[i];   }     // Unites the set that includes i and the set that   // includes j by rank   public void unionByRank(int i, int j)   {   // Find the representatives (or the root nodes) for   // the set that includes i and j   int irep = find(i);   int jrep = find(j);     // Elements are in the same set, no need to unite   // anything   if (irep == jrep) {   return;   }     // Get the rank of i's tree   int irank = rank[irep];     // Get the rank of j's tree   int jrank = rank[jrep];     // If i's rank is less than j's rank   if (irank   // Move i under j   parent[irep] = jrep;   }   // Else if j's rank is less than i's rank   else if (jrank   // Move j under i   parent[jrep] = irep;   }   // Else if their ranks are the same   else {   // Move i under j (doesn't matter which one goes   // where)   parent[irep] = jrep;   // Increment the result tree's rank by 1   rank[jrep]++;   }   }     // Example usage   public static void main(String[] args)   {   int size = 5;   DisjointSet ds = new DisjointSet(size);     // Perform some union operations   ds.unionByRank(0, 1);   ds.unionByRank(2, 3);   ds.unionByRank(1, 3);     // Find the representative of each element and print   // the result   for (int i = 0; i   System.out.println(   'Element ' + i   + ' belongs to the set with representative '  + ds.find(i));   }   }  }>

Python3

class> DisjointSet:> >def> __init__(>self>, size):> >self>.parent>=> [i>for> i>in> range>(size)]> >self>.rank>=> [>0>]>*> size> > ># Function to find the representative (or the root node) of a set> >def> find(>self>, i):> ># If i is not the representative of its set, recursively find the representative> >if> self>.parent[i] !>=> i:> >self>.parent[i]>=> self>.find(>self>.parent[i])># Path compression> >return> self>.parent[i]> > ># Unites the set that includes i and the set that includes j by rank> >def> union_by_rank(>self>, i, j):> ># Find the representatives (or the root nodes) for the set that includes i and j> >irep>=> self>.find(i)> >jrep>=> self>.find(j)> > ># Elements are in the same set, no need to unite anything> >if> irep>=>=> jrep:> >return> > ># Get the rank of i's tree> >irank>=> self>.rank[irep]> > ># Get the rank of j's tree> >jrank>=> self>.rank[jrep]> > ># If i's rank is less than j's rank> >if>

irank   # Move i under j   self.parent[irep] = jrep   # Else if j's rank is less than i's rank   elif jrank   # Move j under i   self.parent[jrep] = irep   # Else if their ranks are the same   else:   # Move i under j (doesn't matter which one goes where)   self.parent[irep] = jrep   # Increment the result tree's rank by 1   self.rank[jrep] += 1    def main(self):   # Example usage   size = 5  ds = DisjointSet(size)     # Perform some union operations   ds.union_by_rank(0, 1)   ds.union_by_rank(2, 3)   ds.union_by_rank(1, 3)     # Find the representative of each element   for i in range(size):   print(f'Element {i} belongs to the set with representative {ds.find(i)}')      # Creating an instance and calling the main method  ds = DisjointSet(size=5)  ds.main()>

C#

using> System;> > class> DisjointSet {> >private> int>[] parent;> >private> int>[] rank;> > >public> DisjointSet(>int> size) {> >parent =>new> int>[size];> >rank =>new> int>[size];> > >// Initialize each element as a separate set> >for> (>int>

i = 0; i   parent[i] = i;   rank[i] = 0;   }   }     // Function to find the representative (or the root node) of a set   private int Find(int i) {   // If i is not the representative of its set, recursively find the representative   if (parent[i] != i) {   parent[i] = Find(parent[i]); // Path compression   }   return parent[i];   }     // Unites the set that includes i and the set that includes j by rank   public void UnionByRank(int i, int j) {   // Find the representatives (or the root nodes) for the set that includes i and j   int irep = Find(i);   int jrep = Find(j);     // Elements are in the same set, no need to unite anything   if (irep == jrep) {   return;   }     // Get the rank of i's tree   int irank = rank[irep];     // Get the rank of j's tree   int jrank = rank[jrep];     // If i's rank is less than j's rank   if (irank   // Move i under j   parent[irep] = jrep;   }   // Else if j's rank is less than i's rank   else if (jrank   // Move j under i   parent[jrep] = irep;   }   // Else if their ranks are the same   else {   // Move i under j (doesn't matter which one goes where)   parent[irep] = jrep;   // Increment the result tree's rank by 1   rank[jrep]++;   }   }     static void Main() {   // Example usage   int size = 5;   DisjointSet ds = new DisjointSet(size);     // Perform some union operations   ds.UnionByRank(0, 1);   ds.UnionByRank(2, 3);   ds.UnionByRank(1, 3);     // Find the representative of each element   for (int i = 0; i   Console.WriteLine('Element ' + i + ' belongs to the set with representative ' + ds.Find(i));   }   }  }>

Javascript

// JavaScript Program for the above approach> unionbyrank(i, j) {> let irep =>this>.find(i);>// Find representative of set including i> let jrep =>this>.find(j);>// Find representative of set including j> > if> (irep === jrep) {> return>;>// Elements are already in the same set> }> > let irank =>this>.rank[irep];>// Rank of set including i> let jrank =>this>.rank[jrep];>// Rank of set including j> > if>

(irank  this.parent[irep] = jrep; // Make j's representative parent of i's representative  } else if (jrank  this.parent[jrep] = irep; // Make i's representative parent of j's representative  } else {  this.parent[irep] = jrep; // Make j's representative parent of i's representative  this.rank[jrep]++; // Increment the rank of the resulting set  }>

Union nach Größe:

Auch hier benötigen wir ein neues Array von Ganzzahlen namens Größe[] . Die Größe dieses Arrays entspricht der des übergeordneten Arrays Elternteil[] . Wenn ich ein Vertreter einer Menge bin, Größe[i] ist die Anzahl der Elemente im Baum, die die Menge darstellen.
Jetzt vereinen wir zwei Bäume (oder Mengen), nennen wir sie links und rechts, dann hängt in diesem Fall alles davon ab Größe links und das Größe von rechts Baum (oder Menge).

Wenn die Größe von links ist kleiner als die Größe von Rechts , dann ist es am besten, umzuziehen links unter rechts und vergrößern Sie die rechte Seite um die linke Seite. Wenn die Größe von rechts kleiner als die Größe von links ist, sollten wir uns auf die gleiche Weise nach rechts unter links bewegen. und vergrößern Sie die linke Seite um die rechte Seite.
Bei gleicher Größe spielt es keine Rolle, welcher Baum unter den anderen kommt.

C++

// Unites the set that includes i and the set> // that includes j by size> > #include> using> namespace> std;> > void> unionBySize(>int> i,>int> j) {> > >// Find the representatives (or the root nodes)> >// for the set that includes i> >int> irep = find(i);> > >// And do the same for the set that includes j> >int> jrep = find(j);> > >// Elements are in the same set, no need to> >// unite anything.> >if> (irep == jrep)> >return>;> > >// Get the size of i’s tree> >int> isize = Size[irep];> > >// Get the size of j’s tree> >int> jsize = Size[jrep];> > >// If i’s size is less than j’s size> >if>

(isize     // Then move i under j   Parent[irep] = jrep;     // Increment j's size by i's size   Size[jrep] += Size[irep];   }     // Else if j’s size is less than i’s size   else {     // Then move j under i   Parent[jrep] = irep;     // Increment i's size by j's size   Size[irep] += Size[jrep];   }  }>

Java

// Java program for the above approach> import> java.util.Arrays;> > class> UnionFind {> > >private> int>[] Parent;> >private> int>[] Size;> > >public> UnionFind(>int> n)> >{> >// Initialize Parent array> >Parent =>new> int>[n];> >for> (>int> i =>0>

; i   Parent[i] = i;   }     // Initialize Size array with 1s   Size = new int[n];   Arrays.fill(Size, 1);   }     // Function to find the representative (or the root   // node) for the set that includes i   public int find(int i)   {   if (Parent[i] != i) {   // Path compression: Make the parent of i the   // root of the set   Parent[i] = find(Parent[i]);   }   return Parent[i];   }     // Unites the set that includes i and the set that   // includes j by size   public void unionBySize(int i, int j)   {   // Find the representatives (or the root nodes) for   // the set that includes i   int irep = find(i);     // And do the same for the set that includes j   int jrep = find(j);     // Elements are in the same set, no need to unite   // anything.   if (irep == jrep)   return;     // Get the size of i’s tree   int isize = Size[irep];     // Get the size of j’s tree   int jsize = Size[jrep];     // If i’s size is less than j’s size   if (isize   // Then move i under j   Parent[irep] = jrep;     // Increment j's size by i's size   Size[jrep] += Size[irep];   }   // Else if j’s size is less than i’s size   else {   // Then move j under i   Parent[jrep] = irep;     // Increment i's size by j's size   Size[irep] += Size[jrep];   }   }  }    public class GFG {     public static void main(String[] args)   {   // Example usage   int n = 5;   UnionFind unionFind = new UnionFind(n);     // Perform union operations   unionFind.unionBySize(0, 1);   unionFind.unionBySize(2, 3);   unionFind.unionBySize(0, 4);     // Print the representative of each element after   // unions   for (int i = 0; i   System.out.println('Element ' + i   + ': Representative = '  + unionFind.find(i));   }   }  }    // This code is contributed by Susobhan Akhuli>

Python3

# Python program for the above approach> class> UnionFind:> >def> __init__(>self>, n):> ># Initialize Parent array> >self>.Parent>=> list>(>range>(n))> > ># Initialize Size array with 1s> >self>.Size>=> [>1>]>*> n> > ># Function to find the representative (or the root node) for the set that includes i> >def> find(>self>, i):> >if> self>.Parent[i] !>=> i:> ># Path compression: Make the parent of i the root of the set> >self>.Parent[i]>=> self>.find(>self>.Parent[i])> >return> self>.Parent[i]> > ># Unites the set that includes i and the set that includes j by size> >def> unionBySize(>self>, i, j):> ># Find the representatives (or the root nodes) for the set that includes i> >irep>=> self>.find(i)> > ># And do the same for the set that includes j> >jrep>=> self>.find(j)> > ># Elements are in the same set, no need to unite anything.> >if> irep>=>=> jrep:> >return> > ># Get the size of i’s tree> >isize>=> self>.Size[irep]> > ># Get the size of j’s tree> >jsize>=> self>.Size[jrep]> > ># If i’s size is less than j’s size> >if>

isize   # Then move i under j   self.Parent[irep] = jrep     # Increment j's size by i's size   self.Size[jrep] += self.Size[irep]   # Else if j’s size is less than i’s size   else:   # Then move j under i   self.Parent[jrep] = irep     # Increment i's size by j's size   self.Size[irep] += self.Size[jrep]    # Example usage  n = 5 unionFind = UnionFind(n)    # Perform union operations  unionFind.unionBySize(0, 1)  unionFind.unionBySize(2, 3)  unionFind.unionBySize(0, 4)    # Print the representative of each element after unions  for i in range(n):   print('Element {}: Representative = {}'.format(i, unionFind.find(i)))    # This code is contributed by Susobhan Akhuli>

C#

using> System;> > class> UnionFind> {> >private> int>[] Parent;> >private> int>[] Size;> > >public> UnionFind(>int> n)> >{> >// Initialize Parent array> >Parent =>new> int>[n];> >for> (>int>

i = 0; i   {   Parent[i] = i;   }     // Initialize Size array with 1s   Size = new int[n];   for (int i = 0; i   {   Size[i] = 1;   }   }     // Function to find the representative (or the root node) for the set that includes i   public int Find(int i)   {   if (Parent[i] != i)   {   // Path compression: Make the parent of i the root of the set   Parent[i] = Find(Parent[i]);   }   return Parent[i];   }     // Unites the set that includes i and the set that includes j by size   public void UnionBySize(int i, int j)   {   // Find the representatives (or the root nodes) for the set that includes i   int irep = Find(i);     // And do the same for the set that includes j   int jrep = Find(j);     // Elements are in the same set, no need to unite anything.   if (irep == jrep)   return;     // Get the size of i’s tree   int isize = Size[irep];     // Get the size of j’s tree   int jsize = Size[jrep];     // If i’s size is less than j’s size   if (isize   {   // Then move i under j   Parent[irep] = jrep;     // Increment j's size by i's size   Size[jrep] += Size[irep];   }   // Else if j’s size is less than i’s size   else  {   // Then move j under i   Parent[jrep] = irep;     // Increment i's size by j's size   Size[irep] += Size[jrep];   }   }  }    class Program  {   static void Main()   {   // Example usage   int n = 5;   UnionFind unionFind = new UnionFind(n);     // Perform union operations   unionFind.UnionBySize(0, 1);   unionFind.UnionBySize(2, 3);   unionFind.UnionBySize(0, 4);     // Print the representative of each element after unions   for (int i = 0; i   {   Console.WriteLine($'Element {i}: Representative = {unionFind.Find(i)}');   }   }  }>

Javascript

unionbysize(i, j) {> >let irep =>this>.find(i);>// Find the representative of the set containing i.> >let jrep =>this>.find(j);>// Find the representative of the set containing j.> > >if> (irep === jrep) {> >return>;>// Elements are already in the same set.> >}> > >let isize =>this>.size[irep];>// Size of the set including i.> >let jsize =>this>.size[jrep];>// Size of the set including j.> > >if>

(isize   // If i's size is less than j's size, make i's representative   // a child of j's representative.   this.parent[irep] = jrep;   this.size[jrep] += this.size[irep]; // Increment j's size by i's size.   } else {   // If j's size is less than or equal to i's size, make j's representative   // a child of i's representative.   this.parent[jrep] = irep;   this.size[irep] += this.size[jrep]; // Increment i's size by j's size.   if (isize === jsize) {   // If sizes are equal, increment the rank of i's representative.   this.rank[irep]++;   }   }   }>

Ausgabe

Element 0: Representative = 0 Element 1: Representative = 0 Element 2: Representative = 2 Element 3: Representative = 2 Element 4: Representative = 0>

Zeitkomplexität : O(log n) ohne Pfadkomprimierung.

Nachfolgend finden Sie die vollständige Implementierung der disjunkten Menge mit Pfadkomprimierung und Vereinigung nach Rang.

C++

// C++ implementation of disjoint set> > #include> using> namespace> std;> > class> DisjSet {> >int> *rank, *parent, n;> > public>:> > >// Constructor to create and> >// initialize sets of n items> >DisjSet(>int> n)> >{> >rank =>new> int>[n];> >parent =>new> int>[n];> >this>->n = n;> >makeSet();> >}> > >// Creates n single item sets> >void> makeSet()> >{> >for> (>int>

i = 0; i   parent[i] = i;   }   }     // Finds set of given item x   int find(int x)   {   // Finds the representative of the set   // that x is an element of   if (parent[x] != x) {     // if x is not the parent of itself   // Then x is not the representative of   // his set,   parent[x] = find(parent[x]);     // so we recursively call Find on its parent   // and move i's node directly under the   // representative of this set   }     return parent[x];   }     // Do union of two sets by rank represented   // by x and y.   void Union(int x, int y)   {   // Find current sets of x and y   int xset = find(x);   int yset = find(y);     // If they are already in same set   if (xset == yset)   return;     // Put smaller ranked item under   // bigger ranked item if ranks are   // different   if (rank[xset]   parent[xset] = yset;   }   else if (rank[xset]>rank[yset]) { parent[yset] = xset;   } // Wenn die Ränge gleich sind, dann erhöhe // den Rang.   else { parent[yset] = xset;   Rang[xset] = Rang[xset] + 1;   } } };    // Treibercode int main() { // Funktionsaufruf DisjSet obj(5);   obj.Union(0, 2);   obj.Union(4, 2);   obj.Union(3, 1);     if (obj.find(4) == obj.find(0)) cout<< 'Yes
';   else  cout << 'No
';   if (obj.find(1) == obj.find(0))   cout << 'Yes
';   else  cout << 'No
';     return 0;  }>

Java

// A Java program to implement Disjoint Set Data> // Structure.> import> java.io.*;> import> java.util.*;> > class> DisjointUnionSets {> >int>[] rank, parent;> >int> n;> > >// Constructor> >public> DisjointUnionSets(>int> n)> >{> >rank =>new> int>[n];> >parent =>new> int>[n];> >this>.n = n;> >makeSet();> >}> > >// Creates n sets with single item in each> >void> makeSet()> >{> >for> (>int> i =>0>

; i   // Initially, all elements are in   // their own set.   parent[i] = i;   }   }     // Returns representative of x's set   int find(int x)   {   // Finds the representative of the set   // that x is an element of   if (parent[x] != x) {   // if x is not the parent of itself   // Then x is not the representative of   // his set,   parent[x] = find(parent[x]);     // so we recursively call Find on its parent   // and move i's node directly under the   // representative of this set   }     return parent[x];   }     // Unites the set that includes x and the set   // that includes x   void union(int x, int y)   {   // Find representatives of two sets   int xRoot = find(x), yRoot = find(y);     // Elements are in the same set, no need   // to unite anything.   if (xRoot == yRoot)   return;     // If x's rank is less than y's rank   if (rank[xRoot]     // Then move x under y so that depth   // of tree remains less   parent[xRoot] = yRoot;     // Else if y's rank is less than x's rank   else if (rank[yRoot]     // Then move y under x so that depth of   // tree remains less   parent[yRoot] = xRoot;     else // if ranks are the same   {   // Then move y under x (doesn't matter   // which one goes where)   parent[yRoot] = xRoot;     // And increment the result tree's   // rank by 1   rank[xRoot] = rank[xRoot] + 1;   }   }  }    // Driver code  public class Main {   public static void main(String[] args)   {   // Let there be 5 persons with ids as   // 0, 1, 2, 3 and 4   int n = 5;   DisjointUnionSets dus =   new DisjointUnionSets(n);     // 0 is a friend of 2   dus.union(0, 2);     // 4 is a friend of 2   dus.union(4, 2);     // 3 is a friend of 1   dus.union(3, 1);     // Check if 4 is a friend of 0   if (dus.find(4) == dus.find(0))   System.out.println('Yes');   else  System.out.println('No');     // Check if 1 is a friend of 0   if (dus.find(1) == dus.find(0))   System.out.println('Yes');   else  System.out.println('No');   }  }>

Python3

# Python3 program to implement Disjoint Set Data> # Structure.> > class> DisjSet:> >def> __init__(>self>, n):> ># Constructor to create and> ># initialize sets of n items> >self>.rank>=> [>1>]>*> n> >self>.parent>=> [i>for> i>in> range>(n)]> > > ># Finds set of given item x> >def> find(>self>, x):> > ># Finds the representative of the set> ># that x is an element of> >if> (>self>.parent[x] !>=> x):> > ># if x is not the parent of itself> ># Then x is not the representative of> ># its set,> >self>.parent[x]>=> self>.find(>self>.parent[x])> > ># so we recursively call Find on its parent> ># and move i's node directly under the> ># representative of this set> > >return> self>.parent[x]> > > ># Do union of two sets represented> ># by x and y.> >def> Union(>self>, x, y):> > ># Find current sets of x and y> >xset>=> self>.find(x)> >yset>=> self>.find(y)> > ># If they are already in same set> >if> xset>=>=> yset:> >return> > ># Put smaller ranked item under> ># bigger ranked item if ranks are> ># different> >if> self>.rank[xset] <>self>.rank[yset]:> >self>.parent[xset]>=> yset> > >elif> self>.rank[xset]>>self>.rank[yset]:> >self>.parent[yset]>=> xset> > ># If ranks are same, then move y under> ># x (doesn't matter which one goes where)> ># and increment rank of x's tree> >else>:> >self>.parent[yset]>=> xset> >self>.rank[xset]>=> self>.rank[xset]>+> 1> > # Driver code> obj>=> DisjSet(>5>)> obj.Union(>0>,>2>)> obj.Union(>4>,>2>)> obj.Union(>3>,>1>)> if> obj.find(>4>)>=>=> obj.find(>0>):> >print>(>'Yes'>)> else>:> >print>(>'No'>)> if> obj.find(>1>)>=>=> obj.find(>0>):> >print>(>'Yes'>)> else>:> >print>(>'No'>)> > # This code is contributed by ng24_7.>

C#

// A C# program to implement> // Disjoint Set Data Structure.> using> System;> > class> DisjointUnionSets> {> >int>[] rank, parent;> >int> n;> > >// Constructor> >public> DisjointUnionSets(>int> n)> >{> >rank =>new> int>[n];> >parent =>new> int>[n];> >this>.n = n;> >makeSet();> >}> > >// Creates n sets with single item in each> >public> void> makeSet()> >{> >for> (>int>

i = 0; i   {   // Initially, all elements are in   // their own set.   parent[i] = i;   }   }     // Returns representative of x's set   public int find(int x)   {   // Finds the representative of the set   // that x is an element of   if (parent[x] != x)   {     // if x is not the parent of itself   // Then x is not the representative of   // his set,   parent[x] = find(parent[x]);     // so we recursively call Find on its parent   // and move i's node directly under the   // representative of this set   }   return parent[x];   }     // Unites the set that includes x and   // the set that includes x   public void union(int x, int y)   {   // Find representatives of two sets   int xRoot = find(x), yRoot = find(y);     // Elements are in the same set,   // no need to unite anything.   if (xRoot == yRoot)   return;     // If x's rank is less than y's rank   if (rank[xRoot]     // Then move x under y so that depth   // of tree remains less   parent[xRoot] = yRoot;     // Else if y's rank is less than x's rank   else if (rank[yRoot]     // Then move y under x so that depth of   // tree remains less   parent[yRoot] = xRoot;     else // if ranks are the same   {   // Then move y under x (doesn't matter   // which one goes where)   parent[yRoot] = xRoot;     // And increment the result tree's   // rank by 1   rank[xRoot] = rank[xRoot] + 1;   }   }  }    // Driver code  class GFG  {   public static void Main(String[] args)   {   // Let there be 5 persons with ids as   // 0, 1, 2, 3 and 4   int n = 5;   DisjointUnionSets dus =   new DisjointUnionSets(n);     // 0 is a friend of 2   dus.union(0, 2);     // 4 is a friend of 2   dus.union(4, 2);     // 3 is a friend of 1   dus.union(3, 1);     // Check if 4 is a friend of 0   if (dus.find(4) == dus.find(0))   Console.WriteLine('Yes');   else  Console.WriteLine('No');     // Check if 1 is a friend of 0   if (dus.find(1) == dus.find(0))   Console.WriteLine('Yes');   else  Console.WriteLine('No');   }  }    // This code is contributed by Rajput-Ji>

Javascript

class DisjSet {> >constructor(n) {> >this>.rank =>new> Array(n);> >this>.parent =>new> Array(n);> >this>.n = n;> >this>.makeSet();> >}> > >makeSet() {> >for> (let i = 0; i <>this>.n; i++) {> >this>.parent[i] = i;> >}> >}> > >find(x) {> >if> (>this>.parent[x] !== x) {> >this>.parent[x] =>this>.find(>this>.parent[x]);> >}> >return> this>.parent[x];> >}> > >Union(x, y) {> >let xset =>this>.find(x);> >let yset =>this>.find(y);> > >if> (xset === yset)>return>;> > >if> (>this>.rank[xset] <>this>.rank[yset]) {> >this>.parent[xset] = yset;> >}>else> if> (>this>.rank[xset]>>this>.rank[yset]) {> >this>.parent[yset] = xset;> >}>else> {> >this>.parent[yset] = xset;> >this>.rank[xset] =>this>.rank[xset] + 1;> >}> >}> }> > // usage example> let obj =>new> DisjSet(5);> obj.Union(0, 2);> obj.Union(4, 2);> obj.Union(3, 1);> > if> (obj.find(4) === obj.find(0)) {> >console.log(>'Yes'>);> }>else> {> >console.log(>'No'>);> }> if> (obj.find(1) === obj.find(0)) {> >console.log(>'Yes'>);> }>else> {> >console.log(>'No'>);> }>

Ausgabe

Yes No>

Zeitkomplexität : O(n) zum Erstellen von n einzelnen Elementmengen. Durch die beiden Techniken – Pfadkomprimierung und Vereinigung nach Rang/Größe – wird die Zeitkomplexität eine nahezu konstante Zeit erreichen. Es stellt sich heraus, dass das Finale amortisierte Zeitkomplexität ist O(α(n)), wobei α(n) die inverse Ackermann-Funktion ist, die sehr stetig wächst (sie überschreitet nicht einmal für n<10).⁶⁰⁰etwa).

Raumkomplexität: O(n), weil wir n Elemente in der disjunkten Mengendatenstruktur speichern müssen.

Einführung in Disjunkte Menge (Union-Find-Algorithmus)

Was ist eine disjunkte Mengendatenstruktur?

Finden Sie heraus, ob x und y zur selben Gruppe gehören oder nicht, d. h. um herauszufinden, ob x und y direkte/indirekte Freunde sind.

Verwendete Datenstrukturen sind:

Operationen an disjunkten Mengendatenstrukturen:

1. Finden Sie:

C++

Java

Python3

C#

Javascript

2. Gewerkschaft:

C++

Java

Python3

C#

Javascript

Optimierungen (Vereinigung nach Rang/Größe und Pfadkomprimierung):

Pfadkomprimierung (Änderungen an Find()):

C++

Java

Python3

C#

Javascript

Union nach Rang :

C++

Java

Python3

C#

Javascript

Union nach Größe:

C++

Java

Python3

C#

Javascript

Nachfolgend finden Sie die vollständige Implementierung der disjunkten Menge mit Pfadkomprimierung und Vereinigung nach Rang.

C++

Java

Python3

C#

Javascript