Inf

Create array of all Inf values

Syntax

X = Inf

X = Inf(n)

X = Inf(sz1,...,szN)

X = Inf(sz)

X = Inf(___,typename)

X = Inf(___,'like',p)

Description

X = Inf returns the scalar representation of positive infinity. Operations return Inf when their result is too large to represent as a floating point number, such as 1/0 or log(0).

For double-precision, Inf represents numbers larger than realmax. For single-precision, Inf represents numbers larger than realmax('single').

X = Inf(n) returns an n-by-n matrix of Inf values.

X = Inf(sz1,...,szN) returns an sz1-by-...-by-szN array of Inf values, where sz1,...,szN indicate the size of each dimension. For example, Inf(3,4) returns a 3-by-4 matrix.

X = Inf(sz) returns an array of Inf values, where the size vector sz defines size(X). For example, Inf([3 4]) returns a 3-by-4 matrix.

X = Inf(___,typename) returns an array of Inf values of data type typename, which can be either 'single' or 'double'.

X = Inf(___,'like',p) returns an array of Inf values of the same data type, sparsity, and complexity (real or complex) as p. You can specify typename or 'like' but not both.

Examples

Matrix of Inf Values

Create a 3-by-3 matrix of Inf values.

X = Inf(3)

X = 3×3

   Inf   Inf   Inf
   Inf   Inf   Inf
   Inf   Inf   Inf

3-D Array of Inf Values

Create a 2-by-3-by-4 array of Inf values and display its size.

X = Inf(2,3,4);
size(X)

ans = 1×3

     2     3     4

Clone Size from Existing Array

Create an array of Inf values that is the same size as an existing array.

A = [1 4; 2 5; 3 6];
sz = size(A);
X = Inf(sz)

X = 3×2

   Inf   Inf
   Inf   Inf
   Inf   Inf

It is a common pattern to combine the previous two lines of code into a single line.

X = Inf(size(A));

Specify Data Type of Inf Values

Create a 1-by-3 vector of Inf values whose elements are of type single.

X = Inf(1,3,'single')

X = 1x3 single row vector

   Inf   Inf   Inf

You can also specify the output type based on the type of another variable. Create a variable p of type single. Then, create a vector of Inf values with the same size and type as p.

p = single([1 2 3]);
X = Inf(size(p),'like',p)

X = 1x3 single row vector

   Inf   Inf   Inf

Input Arguments

n — Size of square matrix

integer

Size of square matrix, specified as an integer.

• If n is 0, then X is an empty matrix.

• If n is negative, then it is treated as 0.

Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

sz1,...,szN — Size of each dimension in a list

integers

Size of each dimension in a list, specified as separate integer arguments.

• If the size of any dimension is 0, then X is an empty array.

• If the size of any dimension is negative, then it is treated as 0.

• Beyond the second dimension, Inf ignores trailing dimensions of length 1. For example, Inf(3,1,1) creates a 3-by-1 vector of Inf values.

Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

sz — Size of each dimension in a vector

row vector of integers

Size of each dimension in a vector, specified as a row vector of integers.

• If the size of any dimension is 0, then X is an empty array.

• If the size of any dimension is negative, then it is treated as 0.

• Beyond the second dimension, Inf ignores trailing dimensions of length 1. For example, Inf([3 1]) creates a 3-by-1 vector of Inf values.

Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

typename — Data type

'double' (default) | single'

Data type to create, specified as 'double' or 'single'.

p — Prototype of array

array

Prototype of array to create, specified as an array.

Data Types: double | single
Complex Number Support: Yes

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• Dimensions must be real, nonnegative, integers.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

The Inf function supports GPU array input with these usage notes and limitations:

• You can specify typename as 'gpuArray'. If you specify typename as 'gpuArray', the default underlying type of the array is double.

  To create a GPU array with underlying type datatype, specify the underlying type as an additional argument before typename. For example, X = Inf(3,datatype,'gpuArray') creates a 3-by-3 GPU array of all Inf values with underlying type datatype.

  You can specify the underlying type datatype as one of these options:

  • 'double'

  • 'single'

• You can also specify the numeric variable p as a gpuArray.

  If you specify p as a gpuArray, the underlying type of the returned array is the same as p.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Usage notes and limitations:

• You can specify typename as 'codistributed' or 'distributed'. If you specify typename as 'codistributed' or 'distributed', the default underlying type of the returned array is double.

  To create a distributed or codistributed array with underlying type datatype, specify the underlying type as an additional argument before typename. For example, X = Inf(3,datatype,'distributed') creates a 3-by-3 distributed array of all Inf values with underlying type datatype.

  You can specify the underlying type datatype as one of these options:

  • 'double'

  • 'single'

• You can also specify p as a codistributed or distributed array.

  If you specify p as a codistributed or distributed array, the underlying type of the returned array is the same as p.

• For additional codistributed syntaxes, see Inf (codistributed) (Parallel Computing Toolbox).

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a