reallog

Natural logarithm for nonnegative real arrays

Syntax

Y = reallog(X)

Description

Y = reallog(X) returns the natural logarithm of each element in array X. Array X must contain only nonnegative real numbers. The size of Y is the same as the size of X.

If X is a table or timetable, then Y is a table or timetable. (since R2023a)

Examples

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Natural Log of Matrix

Open Live Script

Create a 4-by-4 matrix and compute the natural log of each element.

X = magic(4)

X = 4×4

    16     2     3    13
     5    11    10     8
     9     7     6    12
     4    14    15     1

Y = reallog(X)

Y = 4×4

    2.7726    0.6931    1.0986    2.5649
    1.6094    2.3979    2.3026    2.0794
    2.1972    1.9459    1.7918    2.4849
    1.3863    2.6391    2.7081         0

Input Arguments

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`X` — Input
scalar | vector | matrix | multidimensional array | table | timetable

Input, specified as a scalar, vector, matrix, multidimensional array, table, or timetable. The values in X must be nonnegative and real.

Data Types: single | double | table | timetable

Extended Capabilities

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

The reallog function fully supports tall arrays. For more information, see Tall Arrays.

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

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU 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 reallog function supports GPU array input with these usage notes and limitations:

If the output of the function running on the GPU can be complex, then you must explicitly specify its input arguments as complex. For more information, see Work with Complex Numbers on a GPU (Parallel Computing Toolbox).

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™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a

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R2023a: Perform calculations directly on tables and timetables

The reallog function can calculate on all variables within a table or timetable without indexing to access those variables. All variables must have data types that support the calculation. For more information, see Direct Calculations on Tables and Timetables.

reallog

Syntax

Description

Examples

Natural Log of Matrix

Input Arguments

X — Input scalar | vector | matrix | multidimensional array | table | timetable

Extended Capabilities

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

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

GPU Code Generation Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

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

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

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