realmin

Smallest normalized floating-point number

Syntax

f = realmin

f = realmin(precision)

f = realmin(like=p)

Description

f = realmin returns the smallest positive normalized floating-point number in IEEE^® double precision. This is equal to 2^(-1022).

f = realmin(precision) returns the smallest positive normalized floating-point number in IEEE single or double precision. This is equal to realmin for double precision, and to single(2^(-126)) for single precision.

f = realmin(like=p) returns the smallest positive normalized floating-point number with the same data type, sparsity, and complexity (real or complex) as the floating-point variable p.

Examples

Double Precision

Set the output format to long scientific notation. Return the smallest positive normalized floating-point number in IEEE® double precision.

format long e
f = realmin

f = 
    2.225073858507201e-308

Single Precision

Return the smallest positive normalized floating-point number in IEEE® single precision.

f = realmin("single")

f = single

1.1755e-38

Check the class of f.

class(f)

ans = 
'single'

Specify Data Type and Complexity from Existing Array

Return the smallest positive normalized floating-point number with the same data type and complexity as an existing array.

First, create a complex vector of single data type.

p = single([0.12+2i -0.5i 3]);

Return the smallest positive normalized floating-point number as a scalar that is complex like p.

f = realmin(like=p)

f = single

1.1755e-38 +0.0000e+00i

Specify Sparsity from Existing Array

Create a 10-by-10 sparse matrix.

p = sparse(10,10,pi);

Return the smallest positive normalized floating-point number with the same data type and sparsity as p. The output is a 1-by-1 sparse matrix.

f = realmin(like=p)

f = sparse double
   (1,1)     2.2251e-308

Input Arguments

precision — Floating-point precision type

"double" (default) | "single"

Floating-point precision type, specified as "double" or "single".

p — Prototype

floating-point variable

Prototype, specified as a floating-point variable.

Data Types: double | single
Complex Number Support: Yes

Output Arguments

f — Smallest positive normalized floating-point number

scalar

Smallest positive normalized floating-point number, returned as a scalar.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

This function supports tall arrays with the limitations:

• The supported syntax is realmin(like=p), where the underlying data type of p must be a floating-point type.

For more information, see Tall Arrays.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

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

• The supported syntax is realmin(like=p), where the underlying data type of p must be a floating-point type.

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:

• The supported syntax is realmin(like=p), where the underlying data type of p must be a floating-point type.

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

Version History

Introduced before R2006a