log1p
Compute natural logarithm of 1+X
accurately for small
X
Syntax
Description
Examples
Natural Logarithm of 1+X
for Small X
Compare the accuracy of log(1+X)
and log1p(X)
.
Create a vector of small real values.
X = [-1e-16 1e-15 2e-14]
X = 1×3
10-13 ×
-0.0010 0.0100 0.2000
Calculate the natural logarithm of 1+X
using the log
function.
Y = log(1+X)
Y = 1×3
10-13 ×
-0.0011 0.0111 0.1998
The results can be zeros or have large relative errors. For example, Y(2)
is not close to X(2)
, which is 1e-15
.
Y(2)
ans = 1.1102e-15
Calculate the natural logarithm of 1+X
using the log1p
function.
Y = log1p(X)
Y = 1×3
10-13 ×
-0.0010 0.0100 0.2000
In this case, where log1p(X)
is approximately X
, the results are more accurate. For example, Y(2)
is now close to X(2)
, which is 1e-15
.
Y(2)
ans = 1.0000e-15
Input Arguments
X
— Input array
scalar | vector | matrix | multidimensional array | table | timetable
Input array, specified as a scalar, vector, matrix, multidimensional array, table, or timetable.
Data Types: single
| double
| table
| timetable
Complex Number Support: Yes
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
log1p
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 log1p
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 R2006aR2023a: Perform calculations directly on tables and timetables
The log1p
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.
MATLAB 命令
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