Mindste rækkevidde med elementer fra k sorterede lister
Givet et 2D -heltal -array arr [] [] af orden k * n Hvor hver række er sorteret I stigende rækkefølge. Din opgave er at finde det mindste interval, der inkluderer mindst et element fra hver af K lister. Hvis der findes mere end en sådanne intervaller, skal du returnere den første.
Eksempler:
Input: arr [] [] = [[4 7 9 12 15]
[0 8 10 14 20]
[6 12 16 30 50]]
Produktion: 6 8
Forklaring: Den mindste rækkevidde dannes efter nummer 7 fra den første liste 8 fra anden liste og 6 fra den tredje liste.Input: arr [] [] = [[2 4]
[1 7]
[20 40]]
Produktion: 4 20
Forklaring: Området [4 20] indeholder 4 7 20, der indeholder element fra alle de tre arrays.
Indholdstabel
- [Naiv tilgang] - Brug af K -pointer - O (n k^2) Tid og o (k) plads
- [Bedre tilgang] Brug af to markør - o (n*k log (n*k)) tid og o (n*k) plads
- [Effektiv tilgang] - Brug af Min Heap - O (N K Log K) Tid og O (K) Rum
[Naiv tilgang] - Brug af K -pointer - O (n k^2) Tid og o (k) plads
Ideen er at holde K -pointer en for hver liste, der starter ved indeks 0. Ved hvert trin skal du tage Min og Max af de nuværende K -elementer til dannelse af et interval. Til Minimer rækkevidden Vi skal Forøg minværdien Da vi ikke kan reducere de maksimale (alle pointer starter ved 0). Så flyt markøren på listen, der har Nuværende minimum og opdatere rækkevidden. Gentag, indtil en liste er opbrugt.
Trin for trin implementering:
- Opret en liste over tip en for hver inputliste, der starter ved indeks 0.
- Gentag processen Indtil en af pointerne når slutningen af sin liste.
- På hvert trin Vælg de aktuelle elementer Peget af alle pointer.
- Find Minimum og maksimum Blandt disse elementer.
- Beregn rækkevidden ved hjælp af MIN- og MAX -værdierne.
- Hvis dette interval er mindre end den tidligere bedste opdatering svaret.
- Gå videre til markøren af listen, der havde det minimale element.
- Stop, når en liste er opbrugt og returner det bedste sortiment.
// C++ program to find the smallest range // that includes at least one element from // each of the k sorted lists using k pointers #include #include #include using namespace std ; vector < int > findSmallestRange ( vector < vector < int >>& arr ) { int k = arr . size (); int n = arr [ 0 ]. size (); // Pointers for each of the k rows vector < int > ptr ( k 0 ); int minRange = INT_MAX ; int start = -1 end = -1 ; while ( true ) { int minVal = INT_MAX ; int maxVal = INT_MIN ; int minRow = -1 ; // Traverse all k rows to get current min and max for ( int i = 0 ; i < k ; i ++ ) { // If any list is exhausted stop the loop if ( ptr [ i ] == n ) { return { start end }; } // Track min value and its row index if ( arr [ i ][ ptr [ i ]] < minVal ) { minVal = arr [ i ][ ptr [ i ]]; minRow = i ; } // Track current max value if ( arr [ i ][ ptr [ i ]] > maxVal ) { maxVal = arr [ i ][ ptr [ i ]]; } } // Update the result range if a // smaller range is found if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; start = minVal ; end = maxVal ; } // Move the pointer of the // row with minimum value ptr [ minRow ] ++ ; } return { start end }; } int main () { vector < vector < int >> arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; vector < int > res = findSmallestRange ( arr ); cout < < res [ 0 ] < < ' ' < < res [ 1 ]; return 0 ; }
Java // Java program to find the smallest range import java.util.* ; class GfG { static ArrayList < Integer > findSmallestRange ( int [][] arr ) { int k = arr . length ; int n = arr [ 0 ] . length ; // Pointers for each of the k rows int [] ptr = new int [ k ] ; int minRange = Integer . MAX_VALUE ; int start = - 1 end = - 1 ; while ( true ) { int minVal = Integer . MAX_VALUE ; int maxVal = Integer . MIN_VALUE ; int minRow = - 1 ; // Traverse all k rows to get current min and max for ( int i = 0 ; i < k ; i ++ ) { // If any list is exhausted stop the loop if ( ptr [ i ] == n ) { ArrayList < Integer > result = new ArrayList <> (); result . add ( start ); result . add ( end ); return result ; } // Track min value and its row index if ( arr [ i ][ ptr [ i ]] < minVal ) { minVal = arr [ i ][ ptr [ i ]] ; minRow = i ; } // Track current max value if ( arr [ i ][ ptr [ i ]] > maxVal ) { maxVal = arr [ i ][ ptr [ i ]] ; } } // Update the result range if a smaller range is found if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; start = minVal ; end = maxVal ; } // Move the pointer of the row with minimum value ptr [ minRow ]++ ; } } public static void main ( String [] args ) { int [][] arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; ArrayList < Integer > res = findSmallestRange ( arr ); System . out . println ( res . get ( 0 ) + ' ' + res . get ( 1 )); } }
Python # Python program to find the smallest range def findSmallestRange ( arr ): k = len ( arr ) n = len ( arr [ 0 ]) # Pointers for each of the k rows ptr = [ 0 ] * k min_range = float ( 'inf' ) start = - 1 end = - 1 while True : min_val = float ( 'inf' ) max_val = float ( '-inf' ) min_row = - 1 # Traverse all k rows to get current min and max for i in range ( k ): # If any list is exhausted stop the loop if ptr [ i ] == n : return [ start end ] # Track min value and its row index if arr [ i ][ ptr [ i ]] < min_val : min_val = arr [ i ][ ptr [ i ]] min_row = i # Track current max value if arr [ i ][ ptr [ i ]] > max_val : max_val = arr [ i ][ ptr [ i ]] # Update the result range if a smaller range is found if max_val - min_val < min_range : min_range = max_val - min_val start = min_val end = max_val # Move the pointer of the row with minimum value ptr [ min_row ] += 1 if __name__ == '__main__' : arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ] res = findSmallestRange ( arr ) print ( res [ 0 ] res [ 1 ])
C# using System ; using System.Collections.Generic ; class GfG { static List < int > findSmallestRange ( int [] arr ) { int k = arr . GetLength ( 0 ); int n = arr . GetLength ( 1 ); // Pointers for each of the k rows int [] ptr = new int [ k ]; int minRange = int . MaxValue ; int start = - 1 end = - 1 ; while ( true ) { int minVal = int . MaxValue ; int maxVal = int . MinValue ; int minRow = - 1 ; // Traverse all k rows to get current min and max for ( int i = 0 ; i < k ; i ++ ) { // If any list is exhausted stop the loop if ( ptr [ i ] == n ) { return new List < int > { start end }; } int current = arr [ i ptr [ i ]]; if ( current < minVal ) { minVal = current ; minRow = i ; } if ( current > maxVal ) { maxVal = current ; } } // Update the result range if a smaller range is found if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; start = minVal ; end = maxVal ; } // Move the pointer of the row with minimum value ptr [ minRow ] ++ ; } } public static void Main ( string [] args ) { int [] arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; List < int > res = findSmallestRange ( arr ); Console . WriteLine ( res [ 0 ] + ' ' + res [ 1 ]); } }
JavaScript // JavaScript program to find the smallest range function findSmallestRange ( arr ) { let k = arr . length ; let n = arr [ 0 ]. length ; // Pointers for each of the k rows let ptr = new Array ( k ). fill ( 0 ); let minRange = Infinity ; let start = - 1 end = - 1 ; while ( true ) { let minVal = Infinity ; let maxVal = - Infinity ; let minRow = - 1 ; // Traverse all k rows to get current min and max for ( let i = 0 ; i < k ; i ++ ) { // If any list is exhausted stop the loop if ( ptr [ i ] === n ) { return [ start end ]; } // Track min value and its row index if ( arr [ i ][ ptr [ i ]] < minVal ) { minVal = arr [ i ][ ptr [ i ]]; minRow = i ; } // Track current max value if ( arr [ i ][ ptr [ i ]] > maxVal ) { maxVal = arr [ i ][ ptr [ i ]]; } } // Update the result range if a smaller range is found if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; start = minVal ; end = maxVal ; } // Move the pointer of the row with minimum value ptr [ minRow ] ++ ; } } const arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ]; const res = findSmallestRange ( arr ); console . log ( res [ 0 ] + ' ' + res [ 1 ]);
Produktion
6 8
[Bedre tilgang] Brug af to markør - o (n*k log (n*k)) tid og o (n*k) plads
C++Ideen er at finde det mindste intervalproblem ved at omdanne det til et skydevinduesproblem over en fusioneret og sorteret liste over alle elementer fra inputlisterne. Hvert element gemmes sammen med sit originale listeindeks for at spore sin kilde. Efter sortering af den kombinerede liste efter værdi to tip (
leftogright) bruges til at definere et vindue, der bevæger sig gennem listen. Når vinduet udvides, sporer et frekvenskort, hvor mange unikke lister der er repræsenteret. Når vinduet indeholder mindst et nummer fra hver liste, prøver algoritmen at krympe det fra venstre for at finde et mindre gyldigt interval. Det mindste sådanne interval, der findes under denne proces, returneres som resultatet.
#include using namespace std ; vector < int > findSmallestRange ( vector < vector < int >>& arr ) { int k = arr . size (); // Stores the current index for each list vector < int > pointers ( k 0 ); // Stores the current smallest range vector < int > smallestRange = { 0 INT_MAX }; while ( true ) { int currentMin = INT_MAX currentMax = INT_MIN ; int minListIndex = -1 ; // Find the minimum and maximum among current elements of all lists for ( int i = 0 ; i < k ; i ++ ) { int value = arr [ i ][ pointers [ i ]]; if ( value < currentMin ) { currentMin = value ; minListIndex = i ; } if ( value > currentMax ) { currentMax = value ; } } // Update the smallest range if this one is smaller if ( currentMax - currentMin < smallestRange [ 1 ] - smallestRange [ 0 ]) { smallestRange [ 0 ] = currentMin ; smallestRange [ 1 ] = currentMax ; } // Move the pointer in the list that had the minimum value pointers [ minListIndex ] ++ ; // If that list is exhausted break the loop if ( pointers [ minListIndex ] == arr [ minListIndex ]. size ()) break ; } return smallestRange ; } // Driver code int main () { vector < vector < int >> arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; vector < int > result = findSmallestRange ( arr ); cout < < result [ 0 ] < < ' ' < < result [ 1 ]; return 0 ; }
Java import java.util.* ; class GfG { // Function to find the smallest range public static ArrayList < Integer > findSmallestRange ( int [][] arr ) { int k = arr . length ; // Number of lists // Stores the current index for each list int [] pointers = new int [ k ] ; // Stores the current smallest range ArrayList < Integer > smallestRange = new ArrayList <> ( Arrays . asList ( 0 Integer . MAX_VALUE )); // Continue the loop until one list is exhausted while ( true ) { int currentMin = Integer . MAX_VALUE currentMax = Integer . MIN_VALUE ; int minListIndex = - 1 ; // Find the minimum and maximum among current elements of all lists for ( int i = 0 ; i < k ; i ++ ) { int value = arr [ i ][ pointers [ i ]] ; // Update the current minimum if ( value < currentMin ) { currentMin = value ; minListIndex = i ; } // Update the current maximum if ( value > currentMax ) { currentMax = value ; } } // Update the smallest range if this one is smaller if ( currentMax - currentMin < smallestRange . get ( 1 ) - smallestRange . get ( 0 )) { smallestRange . set ( 0 currentMin ); smallestRange . set ( 1 currentMax ); } // Move the pointer in the list that had the minimum value pointers [ minListIndex ]++ ; // If that list is exhausted break the loop if ( pointers [ minListIndex ] == arr [ minListIndex ] . length ) break ; } return smallestRange ; // Return the result as ArrayList } // Driver code public static void main ( String [] args ) { int [][] arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; ArrayList < Integer > result = findSmallestRange ( arr ); System . out . println ( result . get ( 0 ) + ' ' + result . get ( 1 )); } }
Python def findSmallestRange ( arr ): k = len ( arr ) # Number of lists # Stores the current index for each list pointers = [ 0 ] * k # Stores the current smallest range smallestRange = [ 0 float ( 'inf' )] # Continue the loop until one list is exhausted while True : currentMin = float ( 'inf' ) currentMax = - float ( 'inf' ) minListIndex = - 1 # Find the minimum and maximum among current elements of all lists for i in range ( k ): value = arr [ i ][ pointers [ i ]] # Update the current minimum if value < currentMin : currentMin = value minListIndex = i # Update the current maximum if value > currentMax : currentMax = value # Update the smallest range if this one is smaller if currentMax - currentMin < smallestRange [ 1 ] - smallestRange [ 0 ]: smallestRange [ 0 ] = currentMin smallestRange [ 1 ] = currentMax # Move the pointer in the list that had the minimum value pointers [ minListIndex ] += 1 # If that list is exhausted break the loop if pointers [ minListIndex ] == len ( arr [ minListIndex ]): break return smallestRange # Return the result as a list # Driver code if __name__ == '__main__' : arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ] result = findSmallestRange ( arr ) print ( result [ 0 ] result [ 1 ])
C# using System ; using System.Collections.Generic ; class GfG { // Function to find the smallest range public static List < int > findSmallestRange ( int [] arr ) { int k = arr . GetLength ( 0 ); // Number of lists (rows) // Stores the current index for each list (row) int [] pointers = new int [ k ]; // Stores the current smallest range List < int > smallestRange = new List < int > { 0 int . MaxValue }; // Continue the loop until one list is exhausted while ( true ) { int currentMin = int . MaxValue currentMax = int . MinValue ; int minListIndex = - 1 ; // Find the minimum and maximum among current elements // of all lists for ( int i = 0 ; i < k ; i ++ ) { int value = arr [ i pointers [ i ]]; // Update the current minimum if ( value < currentMin ) { currentMin = value ; minListIndex = i ; } // Update the current maximum if ( value > currentMax ) { currentMax = value ; } } // Update the smallest range if this one is smaller if ( currentMax - currentMin < smallestRange [ 1 ] - smallestRange [ 0 ]) { smallestRange [ 0 ] = currentMin ; smallestRange [ 1 ] = currentMax ; } // Move the pointer in the list that had the minimum value pointers [ minListIndex ] ++ ; // If that list is exhausted break the loop if ( pointers [ minListIndex ] == arr . GetLength ( 1 )) break ; } return smallestRange ; // Return the result as List } // Driver code public static void Main ( string [] args ) { int [] arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; List < int > result = findSmallestRange ( arr ); Console . WriteLine ( result [ 0 ] + ' ' + result [ 1 ]); } }
JavaScript function findSmallestRange ( arr ) { const k = arr . length ; // Number of lists // Stores the current index for each list let pointers = new Array ( k ). fill ( 0 ); // Stores the current smallest range let smallestRange = [ 0 Number . MAX_VALUE ]; // Continue the loop until one list is exhausted while ( true ) { let currentMin = Number . MAX_VALUE currentMax = - Number . MAX_VALUE ; let minListIndex = - 1 ; // Find the minimum and maximum among current elements of all lists for ( let i = 0 ; i < k ; i ++ ) { const value = arr [ i ][ pointers [ i ]]; // Update the current minimum if ( value < currentMin ) { currentMin = value ; minListIndex = i ; } // Update the current maximum if ( value > currentMax ) { currentMax = value ; } } // Update the smallest range if this one is smaller if ( currentMax - currentMin < smallestRange [ 1 ] - smallestRange [ 0 ]) { smallestRange [ 0 ] = currentMin ; smallestRange [ 1 ] = currentMax ; } // Move the pointer in the list that had the minimum value pointers [ minListIndex ] ++ ; // If that list is exhausted break the loop if ( pointers [ minListIndex ] === arr [ minListIndex ]. length ) break ; } return smallestRange ; // Return the result as an array } // Driver code const arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ]; const result = findSmallestRange ( arr ); console . log ( result [ 0 ] result [ 1 ]);
Produktion
6 8
[Effektiv tilgang] - Brug af Min Heap - O (N K Log K) Tid og O (K) Rum
Min-heap Kan bruges til at finde minimumsværdien i logaritmisk tid eller log k tid i stedet for lineær tid. For at finde den maksimale værdi initialiserer vi den maksimale værdi af alle 0 indeks oprindeligt. For resten af de maksimale værdier i løkken sammenligner vi simpelthen den aktuelle maksimale værdi med det næste element fra listen, hvorfra min -varen fjernes. Resten af fremgangsmåden forbliver den samme.
Trin for trin implementering:
- Min-heap Kan bruges til at finde minimumsværdien i logaritmisk tid eller log k tid i stedet for lineær tid. For at finde den maksimale værdi initialiserer vi den maksimale værdi af alle 0 indeks oprindeligt. For resten af de maksimale værdier i løkken sammenligner vi simpelthen den aktuelle maksimale værdi med det næste element fra listen, hvorfra min -varen fjernes. Resten af fremgangsmåden forbliver den samme.
Opret en min-heap til at opbevare K-elementer en fra hver matrix og en variabel Minrange initialiseret til en maksimal værdi og opbevar også en variabel maks at gemme det maksimale heltal.
- Min-heap Kan bruges til at finde minimumsværdien i logaritmisk tid eller log k tid i stedet for lineær tid. For at finde den maksimale værdi initialiserer vi den maksimale værdi af alle 0 indeks oprindeligt. For resten af de maksimale værdier i løkken sammenligner vi simpelthen den aktuelle maksimale værdi med det næste element fra listen, hvorfra min -varen fjernes. Resten af fremgangsmåden forbliver den samme.
Sæt oprindeligt det første element fra hver liste og opbevar den maksimale værdi i maks .
- Min-heap Kan bruges til at finde minimumsværdien i logaritmisk tid eller log k tid i stedet for lineær tid. For at finde den maksimale værdi initialiserer vi den maksimale værdi af alle 0 indeks oprindeligt. For resten af de maksimale værdier i løkken sammenligner vi simpelthen den aktuelle maksimale værdi med det næste element fra listen, hvorfra min -varen fjernes. Resten af fremgangsmåden forbliver den samme.
Gentag følgende trin, indtil mindst en liste er udstødning:
- Find minimumsværdien eller min Brug toppen eller roden til min heap, som er det minimale element.
- Opdater nu Minrange Hvis strømmen (max-min) er mindre end Minrange .
- Fjern det øverste eller rodelement fra prioritetskøen Indsæt det næste element fra listen, der indeholder minelementet
- Opdater det maksimale med det nye element, der er indsat, hvis det nye element er større end det forrige maks.
C++ Java #include
Python import java.util.* ; // Class to represent elements in the heap class Node implements Comparable < Node > { int val row col ; Node ( int val int row int col ) { this . val = val ; this . row = row ; this . col = col ; } // For min-heap based on value public int compareTo ( Node other ) { return this . val - other . val ; } } class GfG { // Function to find the smallest range static ArrayList < Integer > findSmallestRange ( int [][] arr ) { int k = arr . length ; int n = arr [ 0 ] . length ; PriorityQueue < Node > pq = new PriorityQueue <> (); int maxVal = Integer . MIN_VALUE ; // Push the first element of each list into the min-heap for ( int i = 0 ; i < k ; i ++ ) { pq . add ( new Node ( arr [ i ][ 0 ] i 0 )); maxVal = Math . max ( maxVal arr [ i ][ 0 ] ); } int minRange = Integer . MAX_VALUE minEl = - 1 maxEl = - 1 ; while ( true ) { Node curr = pq . poll (); int minVal = curr . val ; // Update range if better if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; minEl = minVal ; maxEl = maxVal ; } // If we've reached the end of a list break if ( curr . col + 1 == n ) break ; // Push next element from the same list int nextVal = arr [ curr . row ][ curr . col + 1 ] ; pq . add ( new Node ( nextVal curr . row curr . col + 1 )); maxVal = Math . max ( maxVal nextVal ); } // Return result as ArrayList ArrayList < Integer > result = new ArrayList <> (); result . add ( minEl ); result . add ( maxEl ); return result ; } // Driver code public static void main ( String [] args ) { int [][] arr = { { 4 7 9 12 15 } { 0 8 10 14 20 } { 6 12 16 30 50 } }; ArrayList < Integer > res = findSmallestRange ( arr ); System . out . println ( res . get ( 0 ) + ' ' + res . get ( 1 )); } }
C# import heapq # Function to find the smallest range def findSmallestRange ( arr ): k = len ( arr ) n = len ( arr [ 0 ]) heap = [] maxVal = float ( '-inf' ) # Push the first element of each # list into the min-heap for i in range ( k ): heapq . heappush ( heap ( arr [ i ][ 0 ] i 0 )) maxVal = max ( maxVal arr [ i ][ 0 ]) minRange = float ( 'inf' ) minEl = maxEl = - 1 while True : minVal row col = heapq . heappop ( heap ) # Update range if better if maxVal - minVal < minRange : minRange = maxVal - minVal minEl = minVal maxEl = maxVal # If we've reached the end of a list break if col + 1 == n : break # Push next element from the same list nextVal = arr [ row ][ col + 1 ] heapq . heappush ( heap ( nextVal row col + 1 )) maxVal = max ( maxVal nextVal ) return [ minEl maxEl ] # Driver code if __name__ == '__main__' : arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ] res = findSmallestRange ( arr ) print ( res [ 0 ] res [ 1 ])
JavaScript using System ; using System.Collections.Generic ; // Class to represent elements in the heap class Node : IComparable < Node > { public int val row col ; public Node ( int val int row int col ) { this . val = val ; this . row = row ; this . col = col ; } // For min-heap based on value public int CompareTo ( Node other ) { if ( this . val != other . val ) return this . val . CompareTo ( other . val ); // To avoid duplicate keys in SortedSet if ( this . row != other . row ) return this . row . CompareTo ( other . row ); return this . col . CompareTo ( other . col ); } } class GfG { // Function to find the smallest range static List < int > findSmallestRange ( int [] arr ) { int k = arr . GetLength ( 0 ); int n = arr . GetLength ( 1 ); var pq = new SortedSet < Node > (); int maxVal = int . MinValue ; // Push the first element of each list into the min-heap for ( int i = 0 ; i < k ; i ++ ) { var node = new Node ( arr [ i 0 ] i 0 ); pq . Add ( node ); maxVal = Math . Max ( maxVal arr [ i 0 ]); } int minRange = int . MaxValue minEl = - 1 maxEl = - 1 ; while ( true ) { var curr = GetMin ( pq ); pq . Remove ( curr ); int minVal = curr . val ; // Update range if better if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; minEl = minVal ; maxEl = maxVal ; } // If we've reached the end of a list break if ( curr . col + 1 == n ) break ; // Push next element from the same list int nextVal = arr [ curr . row curr . col + 1 ]; var nextNode = new Node ( nextVal curr . row curr . col + 1 ); pq . Add ( nextNode ); maxVal = Math . Max ( maxVal nextVal ); } return new List < int > { minEl maxEl }; // Return result as List
class Node { constructor ( val row col ) { this . val = val ; this . row = row ; this . col = col ; } } // Function to find the smallest range function findSmallestRange ( arr ) { const k = arr . length ; const n = arr [ 0 ]. length ; const heap = new MinHeap (); let maxVal = - Infinity ; // Push the first element of each list into the min-heap for ( let i = 0 ; i < k ; i ++ ) { heap . push ( new Node ( arr [ i ][ 0 ] i 0 )); maxVal = Math . max ( maxVal arr [ i ][ 0 ]); } let minRange = Infinity ; let minEl = - 1 maxEl = - 1 ; while ( true ) { const curr = heap . pop (); const minVal = curr . val ; // Update range if better if ( maxVal - minVal < minRange ) { minRange = maxVal - minVal ; minEl = minVal ; maxEl = maxVal ; } // If we've reached the end of a list break if ( curr . col + 1 === n ) break ; // Push next element from the same list const nextVal = arr [ curr . row ][ curr . col + 1 ]; heap . push ( new Node ( nextVal curr . row curr . col + 1 )); maxVal = Math . max ( maxVal nextVal ); } return [ minEl maxEl ]; } // Min-heap comparator class MinHeap { constructor () { this . heap = []; } push ( node ) { this . heap . push ( node ); this . _heapifyUp (); } pop () { if ( this . size () === 1 ) return this . heap . pop (); const top = this . heap [ 0 ]; this . heap [ 0 ] = this . heap . pop (); this . _heapifyDown (); return top ; } top () { return this . heap [ 0 ]; } size () { return this . heap . length ; } _heapifyUp () { let idx = this . size () - 1 ; while ( idx > 0 ) { let parent = Math . floor (( idx - 1 ) / 2 ); if ( this . heap [ parent ]. val <= this . heap [ idx ]. val ) break ; [ this . heap [ parent ] this . heap [ idx ]] = [ this . heap [ idx ] this . heap [ parent ]]; idx = parent ; } } _heapifyDown () { let idx = 0 ; const n = this . size (); while ( true ) { let left = 2 * idx + 1 ; let right = 2 * idx + 2 ; let smallest = idx ; if ( left < n && this . heap [ left ]. val < this . heap [ smallest ]. val ) { smallest = left ; } if ( right < n && this . heap [ right ]. val < this . heap [ smallest ]. val ) { smallest = right ; } if ( smallest === idx ) break ; [ this . heap [ smallest ] this . heap [ idx ]] = [ this . heap [ idx ] this . heap [ smallest ]]; idx = smallest ; } } } // Driver code const arr = [ [ 4 7 9 12 15 ] [ 0 8 10 14 20 ] [ 6 12 16 30 50 ] ]; const res = findSmallestRange ( arr ); console . log ( res [ 0 ] + ' ' + res [ 1 ]);
Produktion
6 8
