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Introducció al conjunt disjunt (algoritme Union-Find)

Què és una estructura de dades conjunta?

S'anomenen dos conjunts conjunts discontinus si no tenen cap element en comú, la intersecció de conjunts és un conjunt nul.

Una estructura de dades que emmagatzema un subconjunt d'elements no superposat o disjunt s'anomena estructura de dades de conjunt disjunt. L'estructura de dades del conjunt disjunt admet les operacions següents:



  • Afegint nous conjunts al conjunt disjunt.
  • Combinant conjunts disjunts a un únic conjunt disjunt utilitzant Unió funcionament.
  • Trobar representants d'un conjunt disjunt utilitzant Troba funcionament.
  • Comproveu si dos conjunts són inconjunts o no.

Considereu una situació amb diverses persones i les tasques següents que s'han de realitzar sobre elles:

  • Afegeix a nova amistat relació , és a dir, una persona x es converteix en amiga d'una altra persona, és a dir, afegint un element nou a un conjunt.
  • Trobeu si individual x és amic de l'individu y (amic directe o indirecte)

Exemples:

Ens donen 10 individus diuen, a, b, c, d, e, f, g, h, i, j



Les relacions que s'han d'afegir són les següents:
a b
b d
c f
c i
j e
g j

Es donen preguntes com si a és amic de d o no. Bàsicament hem de crear els quatre grups següents i mantenir una connexió ràpida entre els elements del grup:
G1 = {a, b, d}
G2 = {c, f, i}
G3 = {e,g,j}
G4 = {h}

Esbrineu si x i y pertanyen o no al mateix grup, és a dir, si x i y són amics directes/indirectes.

Particionar els individus en diferents conjunts segons els grups en què pertanyin. Aquest mètode es coneix com a Unió conjunta que manté una col·lecció de Conjunts discontinus i cada conjunt està representat per un dels seus membres.



Per respondre a la pregunta anterior, cal tenir en compte dos punts clau:

  • Com resoldre conjunts? Inicialment, tots els elements pertanyen a conjunts diferents. Després de treballar les relacions donades, seleccionem un membre com a representant . Hi pot haver moltes maneres de seleccionar un representant, una de senzilla és seleccionar amb l'índex més gran.
  • Comproveu si hi ha 2 persones al mateix grup? Si els representants de dues persones són iguals, es faran amics.

Les estructures de dades utilitzades són:

Matriu: S'anomena una matriu de nombres enters Pare[] . Si estem tractant N elements, l'element i de la matriu representa l'element i. Més precisament, l'element i de la matriu Parent[] és el pare de l'element i. Aquestes relacions creen un o més arbres virtuals.

Arbre: És un Conjunt desarticulat . Si dos elements estan al mateix arbre, aleshores estan al mateix Conjunt desarticulat . El node arrel (o el node superior) de cada arbre s'anomena representant del conjunt. Sempre n'hi ha un sol representant únic de cada conjunt. Una regla senzilla per identificar un representant és si 'i' és el representant d'un conjunt, aleshores Pare[i] = i . Si i no és el representant del seu conjunt, es pot trobar viatjant per l'arbre fins que trobem el representant.

Operacions sobre estructures de dades conjuntes:

  1. Troba
  2. Unió

1. Troba:

Es pot implementar recorrent recursivament la matriu pare fins que arribem a un node que és el pare en si mateix.

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>

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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>

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Python 3




# 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>

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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]);> >}> >}> }>

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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> >

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Complexitat temporal : Aquest enfocament és ineficient i pot trigar O(n) temps en el pitjor dels casos.

2. Unió:

Pren dos elements com a entrada i troba els representants dels seus conjunts utilitzant el Troba operació i, finalment, posa qualsevol dels arbres (que representa el conjunt) sota el node arrel de l'altre arbre.

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;> }>

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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); } }>

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Python 3




# 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>

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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); } }>

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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;> }>

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Complexitat temporal : Aquest enfocament és ineficient i podria conduir a un arbre de longitud O(n) en el pitjor dels casos.

Optimitzacions (unió per rang/mida i compressió del camí):

L'eficiència depèn en gran mesura de quin arbre s'uneix a l'altre . Hi ha 2 maneres de fer-ho. El primer és la Unió per rang, que considera l'alçada de l'arbre com a factor i el segon és la Unió per mida, que considera la mida de l'arbre com a factor mentre s'uneix un arbre a l'altre. Aquest mètode juntament amb la compressió del camí ofereix una complexitat de temps gairebé constant.

Compressió del camí (Modificacions a Find()):

Accelera l'estructura de dades comprimint l'alçada dels arbres. Es pot aconseguir inserint un petit mecanisme de memòria cau al fitxer Troba funcionament. Fes una ullada al codi per a més detalls:

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;> >}> }>

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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.>

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Python 3




# 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.>

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C#




programa de matriu bidimensional en c

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.>

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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.>

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Complexitat temporal : O(log n) de mitjana per trucada.

Unió per rang :

En primer lloc, necessitem una nova matriu d'enters anomenada rang[] . La mida d'aquesta matriu és la mateixa que la matriu pare Pare[] . Si i és un representant d'un conjunt, rang [i] és l'alçada de l'arbre que representa el conjunt.
Ara recordeu que en l'operació de la Unió, no importa quin dels dos arbres es mou sota l'altre. Ara el que volem fer és minimitzar l'alçada de l'arbre resultant. Si unim dos arbres (o conjunts), anomenem-los esquerra i dreta, aleshores tot depèn de la rang d'esquerra i la rang de dret .

  • Si el rang de esquerra és inferior al rang de dret , llavors és millor moure's esquerra sota dreta , perquè això no canviarà el rang de la dreta (mentre moure's cap a la dreta per sota de l'esquerra augmentaria l'alçada). De la mateixa manera, si el rang de la dreta és inferior al rang de l'esquerra, hauríem de moure's a la dreta per sota de l'esquerra.
  • Si els rangs són iguals, no importa quin arbre va per sota de l'altre, però el rang del resultat sempre serà un més gran que el rang dels arbres.

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]++; } }>

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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)); } } }>

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Python 3




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()>

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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)); } } }>

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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 }>

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Unió per mida:

De nou, necessitem una nova matriu de nombres enters anomenada mida[] . La mida d'aquesta matriu és la mateixa que la matriu pare Pare[] . Si i és un representant d'un conjunt, mida [i] és el nombre d'elements de l'arbre que representen el conjunt.
Ara estem unint dos arbres (o conjunts), anomenem-los esquerra i dreta, llavors en aquest cas tot depèn de la mida de l'esquerra i la mida de la dreta arbre (o conjunt).

  • Si la mida de esquerra és inferior a la mida de dret , llavors el millor és moure's esquerra sota dreta i augmentar la mida de la dreta per la mida de l'esquerra. De la mateixa manera, si la mida de la dreta és menor que la mida de l'esquerra, hauríem de moure's a la dreta per sota de l'esquerra. i augmentar la mida de l'esquerra per la mida de la dreta.
  • Si les mides són iguals, no importa quin arbre va sota l'altre.

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]; } }>

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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>

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Python 3




# 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>

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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)}'); } } }>

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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]++; } } }>

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Sortida

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

Complexitat temporal : O(log n) sense compressió de camí.

A continuació es mostra la implementació completa del conjunt disjunt amb compressió de camins i unió per 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]>rang[yset]) { pare[yset] = xset; } // Si els rangs són els mateixos, augmenta // el rang. else { pare[yset] = xset; rang[xset] = rang[xset] + 1; } } }; // Codi del controlador int main() { // Crida a la funció 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; }>

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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'); } }>

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Python 3




# 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.>

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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>

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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'>);> }>

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Sortida

Yes No>

Complexitat temporal : O(n) per crear n conjunts d'elements únics. Les dues tècniques -compressió del camí amb la unió per rang/mida, la complexitat del temps arribarà a un temps gairebé constant. Resulta, que la final complexitat temporal amortitzada és O(α(n)), on α(n) és la funció d'Ackermann inversa, que creix de manera molt constant (ni tan sols supera per a n<10600aproximadament).

Complexitat espacial: O(n) perquè necessitem emmagatzemar n elements a l'estructura de dades del conjunt disjunt.