sinpi
Compute sin(X*pi) accurately
Syntax
Description
Examples
Calculate Sine of Multiples of π
Compare the accuracy of sinpi(X)
vs. sin(X*pi)
.
Create a vector of values.
X = [0 1/2 1 3/2 2];
Calculate the sine of X*pi
using the normal sin
function.
Y = sin(X*pi)
Y = 1×5
0 1.0000 0.0000 -1.0000 -0.0000
The results contain small numerical errors due to the fact that pi
is a floating-point approximation of the true value of . For instance, Y(3)
is not exactly zero even though .
Y(3)
ans = 1.2246e-16
Use sinpi
to calculate the same values. In this case, the results are exact.
Z = sinpi(X)
Z = 1×5
0 1 0 -1 0
Z(3)
ans = 0
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
sinpi
function fully supports tall arrays. 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
.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
The sinpi
function
fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray
(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 in R2018bR2023a: Perform calculations directly on tables and timetables
The sinpi
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.
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