VF_sinVD_sinVE_sin
VFx_sinVDx_sinVEx_sin
VFr_sinVDr_sinVEr_sin
VFrx_sinVDrx_sinVErx_sin
VCF_sinVCD_sinVCE_sin
VCFx_sinVCDx_sinVCEx_sin
FunctionSine function
Syntax C/C++#include <VFmath.h>
int VF_sin( fVector Y, fVector X, ui size );
int VFx_sin( fVector Y, fVector X, ui size, float A, float B, float C );
int VFr_sin( fVector Y, fVector X, ui size );
int VFrx_sin( fVector Y, fVector X, ui size, float A, float B, float C );
C++ VecObj#include <OptiVec.h>
int vector<T>::sin( const vector<T>& X );
int vector<T>::x_sin( const vector<T>& X, const T& A, const T& B, const T& C );
int vector<T>::r_sin( const vector<T>& X );
int vector<T>::rx_sin( const vector<T>& X, const T& A, const T& B, const T& C );
Pascal/Delphiuses VFmath;
function VF_sin( Y, X:fVector; size:UIntSize ): IntBool;
function VFx_sin( Y, X:fVector; size:UIntSize; A, B, C:Single ): IntBool;
function VFr_sin( Y, X:fVector; size:UIntSize ): IntBool;
function VFrx_sin( Y, X:fVector; size:UIntSize; A, B, C:Single ): IntBool;
CUDA function C/C++#include <cudaVFmath.h>
int cudaVF_sin( fVector d_Y, fVector d_X, ui size );
int cudaVFx_sin( fVector d_Y, fVector d_X, ui size, float A, float B, float C );
int cusdVFx_sin( fVector d_Y, fVector d_X, ui size, float *d_A, float *d_B, float *d_C );
int VFcu_sin( fVector h_Y, fVector h_X, ui size );
int VFxcu_sin( fVector h_Y, fVector h_X, ui size, float A, float B, float C );
CUDA function Pascal/Delphiuses VFmath;
function cudaVF_sin( d_Y, d_X:fVector; size:UIntSize ): IntBool;
function cudaVFx_sin( d_Y, d_X:fVector; size:UIntSize; A, B, C:Single ): IntBool;
function cusdVFx_sin( d_Y, d_X:fVector; size:UIntSize; d_A, d_B, d_C:PSingle ): IntBool;
function VFcu_sin( h_Y, h_X:fVector; size:UIntSize ): IntBool;
function VFxcu_sin( h_Y, h_X:fVector; size:UIntSize; A, B, C:Single ): IntBool;
Descriptionnormal versions: Yi = sin( Xi )
expanded versions: Yi = C * sin( A*Xi+B )
For large values of Xi, round-off error becomes appreciable; if the Xi values are representable as fractional multiples of p, it is better to use VF_sinrpi than VF_sin.
If, on the other hand, one can be sure that all Xi are within the range -2p <= Xi <= +2p, one can employ the faster reduced-range versions with the prefixes VFr_ and VFrx_. These reduced-range functions are not available for CUDA.
Error handlingPrecision errors lead to a default result of 0.0 and a non-zero return value, but are ignored otherwise; _matherr is not called.
OVERFLOW errors can only occur in the complex versions and lead to a result of ±HUGE_VAL.
Return valueFALSE (0), if no error occurred, otherwise TRUE (non-zero)
See alsoVF_sin2,   VF_sinrpi,   VF_cos,   VF_sinh,   VF_asin,   sin

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