Una array es un objeto de datos bidimensional formado por m filas y n columnas, por lo que tiene valores totales de mxn. Si la mayoría de los elementos de la array tienen valor 0 , entonces se llama array dispersa.
¿Por qué usar array dispersa en lugar de array simple?
- Almacenamiento: hay menos elementos distintos de cero que ceros y, por lo tanto, se puede usar menos memoria para almacenar solo esos elementos.
- Tiempo de cálculo: el tiempo de cálculo se puede ahorrar diseñando lógicamente una estructura de datos que atraviese solo elementos distintos de cero.
Ejemplo:
0 0 3 0 4 0 0 5 7 0 0 0 0 0 0 0 2 6 0 0
La representación de una array dispersa mediante una array 2D conduce al desperdicio de mucha memoria, ya que los ceros en la array no sirven en la mayoría de los casos. Entonces, en lugar de almacenar ceros con elementos distintos de cero, solo almacenamos elementos distintos de cero. Esto significa almacenar elementos distintos de cero con triples (fila, columna, valor).
Las representaciones de arrays dispersas se pueden hacer de muchas maneras, a continuación se muestran dos representaciones comunes:
- representación de array
- Representación de lista enlazada
Método 1: Uso de arrays:
La array 2D se usa para representar una array dispersa en la que hay tres filas nombradas como
- Fila: índice de la fila, donde se encuentra el elemento distinto de cero
- Columna: índice de la columna, donde se encuentra el elemento distinto de cero
- Valor: valor del elemento distinto de cero ubicado en el índice – (fila, columna)
Implementación:
C++
// C++ program for Sparse Matrix Representation // using Array #include <iostream> using namespace std; int main() { // Assume 4x5 sparse matrix int sparseMatrix[4][5] = { {0 , 0 , 3 , 0 , 4 }, {0 , 0 , 5 , 7 , 0 }, {0 , 0 , 0 , 0 , 0 }, {0 , 2 , 6 , 0 , 0 } }; int size = 0; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) if (sparseMatrix[i][j] != 0) size++; // number of columns in compactMatrix (size) must be // equal to number of non - zero elements in // sparseMatrix int compactMatrix[3][size]; // Making of new matrix int k = 0; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) if (sparseMatrix[i][j] != 0) { compactMatrix[0][k] = i; compactMatrix[1][k] = j; compactMatrix[2][k] = sparseMatrix[i][j]; k++; } for (int i=0; i<3; i++) { for (int j=0; j<size; j++) cout <<" "<< compactMatrix[i][j]; cout <<"\n"; } return 0; } // this code is contributed by shivanisinghss2110
C
// C++ program for Sparse Matrix Representation // using Array #include<stdio.h> int main() { // Assume 4x5 sparse matrix int sparseMatrix[4][5] = { {0 , 0 , 3 , 0 , 4 }, {0 , 0 , 5 , 7 , 0 }, {0 , 0 , 0 , 0 , 0 }, {0 , 2 , 6 , 0 , 0 } }; int size = 0; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) if (sparseMatrix[i][j] != 0) size++; // number of columns in compactMatrix (size) must be // equal to number of non - zero elements in // sparseMatrix int compactMatrix[3][size]; // Making of new matrix int k = 0; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) if (sparseMatrix[i][j] != 0) { compactMatrix[0][k] = i; compactMatrix[1][k] = j; compactMatrix[2][k] = sparseMatrix[i][j]; k++; } for (int i=0; i<3; i++) { for (int j=0; j<size; j++) printf("%d ", compactMatrix[i][j]); printf("\n"); } return 0; }
Java
// Java program for Sparse Matrix Representation // using Array class GFG { public static void main(String[] args) { int sparseMatrix[][] = { {0, 0, 3, 0, 4}, {0, 0, 5, 7, 0}, {0, 0, 0, 0, 0}, {0, 2, 6, 0, 0} }; int size = 0; for (int i = 0; i < 4; i++) { for (int j = 0; j < 5; j++) { if (sparseMatrix[i][j] != 0) { size++; } } } // number of columns in compactMatrix (size) must be // equal to number of non - zero elements in // sparseMatrix int compactMatrix[][] = new int[3][size]; // Making of new matrix int k = 0; for (int i = 0; i < 4; i++) { for (int j = 0; j < 5; j++) { if (sparseMatrix[i][j] != 0) { compactMatrix[0][k] = i; compactMatrix[1][k] = j; compactMatrix[2][k] = sparseMatrix[i][j]; k++; } } } for (int i = 0; i < 3; i++) { for (int j = 0; j < size; j++) { System.out.printf("%d ", compactMatrix[i][j]); } System.out.printf("\n"); } } } /* This code contributed by PrinciRaj1992 */
Python3
# Python program for Sparse Matrix Representation # using arrays # assume a sparse matrix of order 4*5 # let assume another matrix compactMatrix # now store the value,row,column of arr1 in sparse matrix compactMatrix sparseMatrix = [[0,0,3,0,4],[0,0,5,7,0],[0,0,0,0,0],[0,2,6,0,0]] # initialize size as 0 size = 0 for i in range(4): for j in range(5): if (sparseMatrix[i][j] != 0): size += 1 # number of columns in compactMatrix(size) should # be equal to number of non-zero elements in sparseMatrix rows, cols = (3, size) compactMatrix = [[0 for i in range(cols)] for j in range(rows)] k = 0 for i in range(4): for j in range(5): if (sparseMatrix[i][j] != 0): compactMatrix[0][k] = i compactMatrix[1][k] = j compactMatrix[2][k] = sparseMatrix[i][j] k += 1 for i in compactMatrix: print(i) # This code is contributed by MRINALWALIA
C#
// C# program for Sparse Matrix Representation // using Array using System; class Program { static void Main(string[] args) { // Assume 4x5 sparse matrix int[, ] sparseMatrix = new int[4, 5] { { 0, 0, 3, 0, 4 }, { 0, 0, 5, 7, 0 }, { 0, 0, 0, 0, 0 }, { 0, 2, 6, 0, 0 } }; int size = 0; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) if (sparseMatrix[i, j] != 0) size++; // number of columns in compactMatrix (size) must be // equal to number of non - zero elements in // sparseMatrix int[, ] compactMatrix = new int[3, size]; // Making of new matrix int k = 0; for (int i = 0; i < 4; i++) { for (int j = 0; j < 5; j++) if (sparseMatrix[i, j] != 0) { compactMatrix[0, k] = i; compactMatrix[1, k] = j; compactMatrix[2, k] = sparseMatrix[i, j]; k++; } } for (int i = 0; i < 3; i++) { for (int j = 0; j < size; j++) Console.Write(" " + compactMatrix[i, j]); Console.WriteLine(); } } } // This code is contributed by Tapesh(tapeshdua420)
0 0 1 1 3 3 2 4 2 3 1 2 3 4 5 7 2 6
Método 2: uso de listas vinculadas
En la lista vinculada, cada Node tiene cuatro campos. Estos cuatro campos se definen como:
- Fila: índice de la fila, donde se encuentra el elemento distinto de cero
- Columna: índice de la columna, donde se encuentra el elemento distinto de cero
- Valor: valor del elemento distinto de cero ubicado en el índice – (fila, columna)
- Node siguiente: Dirección del Node siguiente
C++
// C++ program for sparse matrix representation. // Using Link list #include<iostream> using namespace std; // Node class to represent link list class Node { public: int row; int col; int data; Node *next; }; // Function to create new node void create_new_node(Node **p, int row_index, int col_index, int x) { Node *temp = *p; Node *r; // If link list is empty then // create first node and assign value. if (temp == NULL) { temp = new Node(); temp->row = row_index; temp->col = col_index; temp->data = x; temp->next = NULL; *p = temp; } // If link list is already created // then append newly created node else { while (temp->next != NULL) temp = temp->next; r = new Node(); r->row = row_index; r->col = col_index; r->data = x; r->next = NULL; temp->next = r; } } // Function prints contents of linked list // starting from start void printList(Node *start) { Node *ptr = start; cout << "row_position:"; while (ptr != NULL) { cout << ptr->row << " "; ptr = ptr->next; } cout << endl; cout << "column_position:"; ptr = start; while (ptr != NULL) { cout << ptr->col << " "; ptr = ptr->next; } cout << endl; cout << "Value:"; ptr = start; while (ptr != NULL) { cout << ptr->data << " "; ptr = ptr->next; } } // Driver Code int main() { // 4x5 sparse matrix int sparseMatrix[4][5] = { { 0 , 0 , 3 , 0 , 4 }, { 0 , 0 , 5 , 7 , 0 }, { 0 , 0 , 0 , 0 , 0 }, { 0 , 2 , 6 , 0 , 0 } }; // Creating head/first node of list as NULL Node *first = NULL; for(int i = 0; i < 4; i++) { for(int j = 0; j < 5; j++) { // Pass only those values which // are non - zero if (sparseMatrix[i][j] != 0) create_new_node(&first, i, j, sparseMatrix[i][j]); } } printList(first); return 0; } // This code is contributed by ronaksuba
C
// C program for Sparse Matrix Representation // using Linked Lists #include<stdio.h> #include<stdlib.h> // Node to represent sparse matrix struct Node { int value; int row_position; int column_postion; struct Node *next; }; // Function to create new node void create_new_node(struct Node** start, int non_zero_element, int row_index, int column_index ) { struct Node *temp, *r; temp = *start; if (temp == NULL) { // Create new node dynamically temp = (struct Node *) malloc (sizeof(struct Node)); temp->value = non_zero_element; temp->row_position = row_index; temp->column_postion = column_index; temp->next = NULL; *start = temp; } else { while (temp->next != NULL) temp = temp->next; // Create new node dynamically r = (struct Node *) malloc (sizeof(struct Node)); r->value = non_zero_element; r->row_position = row_index; r->column_postion = column_index; r->next = NULL; temp->next = r; } } // This function prints contents of linked list // starting from start void PrintList(struct Node* start) { struct Node *temp, *r, *s; temp = r = s = start; printf("row_position: "); while(temp != NULL) { printf("%d ", temp->row_position); temp = temp->next; } printf("\n"); printf("column_postion: "); while(r != NULL) { printf("%d ", r->column_postion); r = r->next; } printf("\n"); printf("Value: "); while(s != NULL) { printf("%d ", s->value); s = s->next; } printf("\n"); } // Driver of the program int main() { // Assume 4x5 sparse matrix int sparseMatric[4][5] = { {0 , 0 , 3 , 0 , 4 }, {0 , 0 , 5 , 7 , 0 }, {0 , 0 , 0 , 0 , 0 }, {0 , 2 , 6 , 0 , 0 } }; /* Start with the empty list */ struct Node* start = NULL; for (int i = 0; i < 4; i++) for (int j = 0; j < 5; j++) // Pass only those values which are non - zero if (sparseMatric[i][j] != 0) create_new_node(&start, sparseMatric[i][j], i, j); PrintList(start); return 0; }
Java
// Java program for sparse matrix representation. // Using Link list import java.util.*; public class SparseMatrix { // Creating head/first node of list as NULL static Node first = null; // Node class to represent link list public static class Node { int row; int col; int data; Node next; }; // Driver Code public static void main(String[] args) { // 4x5 sparse matrix int[][] sparseMatrix = { { 0, 0, 3, 0, 4 }, { 0, 0, 5, 7, 0 }, { 0, 0, 0, 0, 0 }, { 0, 2, 6, 0, 0 } }; for (int i = 0; i < 4; i++) { for (int j = 0; j < 5; j++) { // Pass only those values which // are non - zero if (sparseMatrix[i][j] != 0) { create_new_node(i, j, sparseMatrix[i][j]); } } } printList(first); } // Function to create new node private static void create_new_node(int row_index, int col_index, int x) { Node temp = first; Node r; // If link list is empty then // create first node and assign value. if (temp == null) { temp = new Node(); temp.row = row_index; temp.col = col_index; temp.data = x; temp.next = null; first = temp; } // If link list is already created // then append newly created node else { while (temp.next != null) temp = temp.next; r = new Node(); r.row = row_index; r.col = col_index; r.data = x; r.next = null; temp.next = r; } } // Function prints contents of linked list // starting from start public static void printList(Node start) { Node ptr = start; System.out.print("row_position:"); while (ptr != null) { System.out.print(ptr.row + " "); ptr = ptr.next; } System.out.println(""); System.out.print("column_position:"); ptr = start; while (ptr != null) { System.out.print(ptr.col + " "); ptr = ptr.next; } System.out.println(""); System.out.print("Value:"); ptr = start; while (ptr != null) { System.out.print(ptr.data + " "); ptr = ptr.next; } } } // This code is contributed by Tapesh (tapeshdua420)
Python3
# Python Program for Representation of # Sparse Matrix into Linked List # Node Class to represent Linked List Node class Node: # Making the slots for storing row, # column, value, and address __slots__ = "row", "col", "data", "next" # Constructor to initialize the values def __init__(self, row=0, col=0, data=0, next=None): self.row = row self.col = col self.data = data self.next = next # Class to convert Sparse Matrix # into Linked List class Sparse: # Initialize Class Variables def __init__(self): self.head = None self.temp = None self.size = 0 # Function which returns the size # of the Linked List def __len__(self): return self.size # Check the Linked List is # Empty or not def isempty(self): return self.size == 0 # Responsible function to create # Linked List from Sparse Matrix def create_new_node(self, row, col, data): # Creating New Node newNode = Node(row, col, data, None) # Check whether the List is # empty or not if self.isempty(): self.head = newNode else: self.temp.next = newNode self.temp = newNode # Incrementing the size self.size += 1 # Function display the contents of # Linked List def PrintList(self): temp = r = s = self.head print("row_position:", end=" ") while temp != None: print(temp.row, end=" ") temp = temp.next print() print("column_postion:", end=" ") while r != None: print(r.col, end=" ") r = r.next print() print("Value:", end=" ") while s != None: print(s.data, end=" ") s = s.next print() # Driver Code if __name__ == "__main__": # Creating Object s = Sparse() # Assuming 4x5 Sparse Matrix sparseMatric = [[0, 0, 3, 0, 4], [0, 0, 5, 7, 0], [0, 0, 0, 0, 0], [0, 2, 6, 0, 0]] for i in range(4): for j in range(5): # Creating Linked List by only those # elements which are non-zero if sparseMatric[i][j] != 0: s.create_new_node(i, j, sparseMatric[i][j]) # Printing the Linked List Representation # of the sparse matrix s.PrintList() # This code is contributed by Naveen Rathore
C#
// C# program for sparse matrix representation. // Using Link list using System; class Program { // Creating head/first node of list as NULL static Node first = null; // Node class to represent link list public class Node { public int row; public int col; public int data; public Node next; }; // Driver Code static void Main(string[] args) { // 4x5 sparse matrix int[, ] sparseMatrix = { { 0, 0, 3, 0, 4 }, { 0, 0, 5, 7, 0 }, { 0, 0, 0, 0, 0 }, { 0, 2, 6, 0, 0 } }; for (int i = 0; i < 4; i++) { for (int j = 0; j < 5; j++) { // Pass only those values which // are non - zero if (sparseMatrix[i, j] != 0) { create_new_node(i, j, sparseMatrix[i, j]); } } } printList(first); } // Function to create new node private static void create_new_node(int row_index, int col_index, int x) { Node temp = first; Node r; // If link list is empty then // create first node and assign value. if (temp == null) { temp = new Node(); temp.row = row_index; temp.col = col_index; temp.data = x; temp.next = null; first = temp; } // If link list is already created // then append newly created node else { while (temp.next != null) temp = temp.next; r = new Node(); r.row = row_index; r.col = col_index; r.data = x; r.next = null; temp.next = r; } } // Function prints contents of linked list // starting from start public static void printList(Node start) { Node ptr = start; Console.Write("row_position:"); while (ptr != null) { Console.Write(ptr.row + " "); ptr = ptr.next; } Console.WriteLine(""); Console.Write("column_position:"); ptr = start; while (ptr != null) { Console.Write(ptr.col + " "); ptr = ptr.next; } Console.WriteLine(""); Console.Write("Value:"); ptr = start; while (ptr != null) { Console.Write(ptr.data + " "); ptr = ptr.next; } } } // This code is contributed by Tapesh (tapeshdua420)
row_position:0 0 1 1 3 3 column_position:2 4 2 3 1 2 Value:3 4 5 7 2 6
Otras representaciones:
Como un diccionario donde los números de fila y columna se usan como claves y los valores son entradas de array. Este método ahorra espacio pero el acceso secuencial de elementos es costoso.
Como una lista de lista . La idea es hacer una lista de filas y cada elemento de la lista contiene valores. Podemos mantener los elementos de la lista ordenados por números de columna.
Sparse Matrix y sus representaciones | Conjunto 2 (usando la lista de listas y el diccionario de claves)
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Publicación traducida automáticamente
Artículo escrito por GeeksforGeeks-1 y traducido por Barcelona Geeks. The original can be accessed here. Licence: CCBY-SA