How to Create Array of Zeros in MATLAB

Ammar Ali Feb 12, 2024
  1. Create Arrays of Zeros in MATLAB Using the zeros() Function
  2. Create Sparse Arrays of Zeros in MATLAB Using the sparse() Function
  3. Conclusion
How to Create Array of Zeros in MATLAB

MATLAB, a powerful numerical computing environment, provides a multitude of tools for data manipulation and analysis. One fundamental operation frequently encountered in MATLAB programming is the creation of arrays.

In this article, we will explore the various ways to create an array of zeros in MATLAB.

Create Arrays of Zeros in MATLAB Using the zeros() Function

MATLAB simplifies the task of generating arrays filled with zeros with the zeros() function.

The zeros() function in MATLAB is designed to generate an array filled with zeros. It takes one or more arguments to specify the dimensions of the array.

The basic syntax is as follows:

MATLAB
 matlabCopyZ = zeros(m, n);

Here, Z is the output array of size m-by-n filled with zeros. The function can also take additional arguments to create arrays with more than two dimensions.

For example:

MATLAB
 matlabCopyZ = zeros(m, n, p, ...);

This creates a multidimensional array with dimensions m, n, p, and so on, filled with zeros.

Example 1: Creating a Square Matrix

MATLAB
 matlabCopy% Creating a 3x3 matrix of zeros
ZeroMatrix = zeros(3);
ZeroMatrix

In this example, we demonstrate the fundamental use of the zeros() function to create a 3x3 matrix filled with zeros. The code simply calls zeros(3), where the single scalar input denotes the dimensions of the desired square matrix.

The resulting matrix, stored in the variable ZeroMatrix, is displayed as:

 textCopyZeroMatrix =

   0   0   0
   0   0   0
   0   0   0

This straightforward example demonstrates the basic usage of the zeros() function for creating square matrices.

Example 2: Specifying Dimensions as a Vector

MATLAB
 matlabCopy% Creating a 2x3 matrix of zeros
ZeroMatrix = zeros([2 3]);
ZeroMatrix

Here, we showcase the flexibility of the zeros() function by passing a vector [2 3] as input, generating a 2x3 matrix of zeros. The line ZeroMatrix = zeros([2 3]) initializes a matrix with the specified dimensions, and the output is:

Output:

 textCopyZeroMatrix =

   0   0   0
   0   0   0

This example illustrates how to define non-square matrix dimensions using the zeros() function.

Example 3: Creating a 3D Array

MATLAB
 matlabCopy% Creating a 1x2x3 3D matrix of zeros
ZeroMatrix = zeros(1, 2, 3);
ZeroMatrix

To highlight the ability of the zeros() function to handle multiple scalar inputs, we create a 3D matrix of size 1x2x3. The line ZeroMatrix = zeros(1, 2, 3) results in a three-dimensional array, and the output showcases the structure.

Output:

 textCopyZeroMatrix =

ans(:,:,1) =

   0   0

ans(:,:,2) =

   0   0

ans(:,:,3) =

   0   0

This example illustrates the versatility of the zeros() function in generating multi-dimensional arrays.

Example 4: Copying Size From Another Matrix

MATLAB
 matlabCopy% Creating a matrix and a matrix of zeros with the same size
originalMatrix = [1 2; 3 6];
ZeroMatrix = zeros(size(originalMatrix));
originalMatrix
ZeroMatrix

In this example, we explore how to create a matrix of zeros with the same dimensions as an existing matrix (originalMatrix). By utilizing the size() function, we retrieve the size information and pass it to the zeros() function.

The output reveals the creation of a new matrix filled with zeros but sharing the dimensions of originalMatrix.

Output:

 textCopyoriginalMatrix =

   1   2
   3   6

ZeroMatrix =

   0   0
   0   0

This example demonstrates how to create a matrix of zeros with dimensions matching an existing matrix.

Example 5: Specifying Data Type

MATLAB
 matlabCopy% Creating a matrix of zeros with a specified data type
originalMatrix = int16([1 2 3 6]);
ZeroMatrix = zeros(size(originalMatrix), 'like', originalMatrix);
originalMatrix
ZeroMatrix

This example illustrates the like property within the zeros() function, allowing us to create a matrix of zeros with the same data type as another matrix (originalMatrix). By using int16 as the data type, the resulting ZeroMatrix maintains consistency.

Output:

 textCopyoriginalMatrix =

  1×4 int16 row vector

   1   2   3   6

ZeroMatrix =

  1×4 int16 row vector

   0   0   0   0

This example highlights how to maintain consistent data types when creating matrices using the zeros() function.

Example 6: Specifying Data Type Directly

MATLAB
 matlabCopy% Creating a matrix of zeros with a specified data type
originalMatrix = [1 2 3 6];
ZeroMatrix = zeros(size(originalMatrix), 'int8');
originalMatrix
ZeroMatrix

Here, we directly specify the data type (int8) within the zeros() function. The code ZeroMatrix = zeros(size(originalMatrix), 'int8') creates a matrix filled with zeros of the specified data type.

Output:

 textCopyoriginalMatrix =

   1   2   3   6

ZeroMatrix =

  0  0  0  0

This example provides an alternative method for explicitly specifying data types during matrix creation.

Example 7: Using Colon Operator

MATLAB
 matlabCopy% Creating a vector of zeros using the colon operator
indices = 1:10;
ZeroVector = zeros(size(indices));
ZeroVector

In this final example, we showcase an alternative approach to create a vector of zeros. The colon operator generates indices (1 through 10), and the zeros() function is employed to initialize a vector of zeros with the same size as the indices.

Output:

 textCopyZeroVector =

   0   0   0   0   0   0   0   0   0   0

This example provides an alternative approach for creating arrays of zeros using the colon operator and the zeros() function.

The zeros() function in MATLAB provides a flexible and efficient way to create arrays filled with zeros. Whether you need a simple matrix, a multi-dimensional array, or a specific data type, the zeros() function is a valuable tool for array initialization in MATLAB.

Create Sparse Arrays of Zeros in MATLAB Using the sparse() Function

In addition to the zeros() function, MATLAB offers another powerful tool for generating arrays of zeros with a specialized purpose - the sparse() function.

The sparse() function is particularly useful for dealing with large matrices that are predominantly filled with zeros. It creates a sparse matrix, a data structure that only stores non-zero elements, resulting in significant memory savings and computational efficiency.

The basic syntax is as follows:

MATLAB
 matlabCopyS = sparse(i, j, s, m, n);

Where:

  • i: Vector of row indices for the non-zero elements.
  • j: Vector of column indices for the non-zero elements.
  • s: Vector of the non-zero elements.
  • m: Number of rows in the matrix.
  • n: Number of columns in the matrix.

In the context of creating an array of zeros, the s parameter is not explicitly required, as we are interested in generating a matrix filled with zeros. The i and j vectors specify the positions of the non-zero elements, and m and n define the size of the matrix.

Example 1: Creating a Sparse Matrix

MATLAB
 matlabCopy% Creating a sparse 3x3 matrix of zeros
SparseMatrix = sparse(3, 3);
SparseMatrix

In this example, we illustrate the fundamental use of the sparse() function to create a sparse matrix filled with zeros. The code SparseMatrix = sparse(3, 3) generates a sparse 3x3 matrix efficiently representing only the zeros.

The resulting SparseMatrix is displayed, showcasing the memory-efficient sparse representation.

Output:

 textCopySparseMatrix =

   All zero sparse: 3×3

Example 2: Creating a Sparse Vector

MATLAB
 matlabCopy% Creating a sparse row vector of zeros
SparseVector = sparse(1, 5);
SparseVector

Here, we demonstrate creating a sparse row vector using sparse(1, 5). The resulting SparseVector efficiently represents a row vector with zeros, storing only the information about the non-zero elements.

This is particularly useful for large vectors with mostly zero elements.

Output:

 textCopySparseVector =
   (1,1)        0   (1,2)        0   (1,3)        0   (1,4)        0   (1,5)        0

Example 3: Creating a Sparse Matrix With Non-Zero Elements

MATLAB
 matlabCopy% Creating a sparse 4x4 matrix with some non-zero elements
SparseNonZero = sparse([1, 3, 2], [2, 4, 3], [5, 8, 1], 4, 4);
SparseNonZero

In this example, we showcase the ability of the sparse() function to handle matrices with non-zero elements. The input vectors [1, 3, 2], [2, 4, 3], and [5, 8, 1] represent the row indices, column indices, and values, respectively.

The resulting SparseNonZero matrix efficiently represents only the provided non-zero elements.

Output:

 textCopySparseNonZero =

Compressed Column Sparse (rows = 4, cols = 4, nnz = 3 [19%])

  (1, 2) ->  5
  (2, 3) ->  1
  (3, 4) ->  8

Example 4: Creating a Sparse Matrix From a Dense Matrix

MATLAB
 matlabCopy% Creating a sparse matrix from a dense matrix
DenseMatrix = eye(3);
SparseFromDense = sparse(DenseMatrix);
SparseFromDense

Here, we demonstrate how to convert a dense matrix to a sparse matrix using the sparse() function. The code SparseFromDense = sparse(DenseMatrix) takes a dense identity matrix (eye(3)) and efficiently creates a sparse representation, resulting in the SparseFromDense matrix.

Output:

 textCopySparseFromDense =

Compressed Column Sparse (rows = 3, cols = 3, nnz = 3 [33%])

  (1, 1) ->  1
  (2, 2) ->  1
  (3, 3) ->  1

The sparse() function in MATLAB provides an efficient way to handle matrices with a significant number of zero elements. By only storing non-zero elements along with their indices, sparse matrices save memory and computational resources, making them ideal for large-scale applications.

Conclusion

Creating arrays of zeros in MATLAB is a straightforward process that can be accomplished using the zeros() function or, for sparse matrices, the sparse() function.

The zeros() function is versatile, allowing for the creation of arrays with various dimensions and data types. Whether you need a simple matrix, a multi-dimensional array, or a specific data type, the zeros() function caters to diverse requirements.

Additionally, the sparse() function provides an efficient way to handle matrices with a significant number of zero elements, optimizing memory usage and computational resources. By creating sparse representations of matrices, MATLAB users can enhance the efficiency of operations on large-scale data sets.

Author: Ammar Ali
Ammar Ali avatar Ammar Ali avatar

Hello! I am Ammar Ali, a programmer here to learn from experience, people, and docs, and create interesting and useful programming content. I mostly create content about Python, Matlab, and Microcontrollers like Arduino and PIC.

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