Do interpolation with mode of Linear, Spline or B-Spline.
int ocmath_interpolate( const double * pX, double * pY, UINT nSize, const double * pSrcX, const double * pSrcY, UINT nSrcSize, int nMode = INTERP_TYPE_LINEAR, double dSmoothingFactor = 1, const double * pWeights = NULL, double * pCof = NULL, DWORD dwCntrl = 0, int nSplBoundType = 0, int iOption = OPTION_EXTRAPOLATE )
- [input] pointer to X coordinate to be evaluated. size is nSize
- [output] pointer to the interpolation values at evaluation points. size is nSize
- if pX[i] is invalid(e.g, out of the range of pSrcX to pSrcX[nSrcSize-1] in linear interpolation), set pY[i] to NANUM.
- [input] size of pX and pY, nSize > 0
- [input] pointer to the X value of the curve, must be in strictly ascending order, otherwise it should be sorted before calling this function. size is nSrcSize.
- [input] pointer to the Y value of the curve. size is nSrcSize.
- [input] size of pSrcX and pSrcY. if nMode = INTERP_TYPE_LINEAR, nSrcSize >= 1; otherwise nSrcSize >= 4.
- [input] interpolation method. Must be one of the three modes:
- INTERP_TYPE_LINEAR(linear interpolation),
- INTERP_TYPE_SPLINE(cubic spline interpolation with not-a-knot boundary condition, and the not-a-knot boundary condition assume that the 3rd order derivative are continuous on the 2nd and last 2nd points),
- INTERP_TYPE_BSPLINE(B-Spline curve fitting using method by Dierckx.P)
- [input] This argument specifies the closeness to the original data. It is only useful when nMode = INTERP_TYPE_BSPLINE. dSmoothingFactor >= 0.
- By means of this parameter, the user can control the tradeoff between closeness of fit and smoothness of fit of the approximation.
- If dSmoothingFactor is too large, the spline will be too smooth and signal will be lost ; if it is too small the spline will pick up too much noise.
- In the extreme cases the program will return an interpolating spline if dSmoothingFactor=0 and the weighted least-squares polynomial of degree 3 if s is very large.
- [input] pointer to weights, which is only used in method INTERP_TYPE_BSPLINE, by default(pWeights = NULL) all weights are 1. size is nSrcSize
- [output] pointer to coefficients, which are used in method INTERP_TYPE_SPLINE and INTERP_TYPE_BSPLINE, by default(pCof = Null), size is nSrcSize
- [input] indicates do sorting or not before doing interpolation, when it equals OCMATH_SRCDATA_X_MONOTONIC, don't sort.
- [input] enumeration, indicate the boundary condition for spline (cubic spline), 0 for natural boundary condition, 1 for not_a_knot (currently only support these 2 kinds)
- [input] enumeration, specify how to extrapolate Y values in extrapolated range. Must be one of the three values:
- OPTION_EXTRAPOLATE(extrapolate Y using the last two points),
- OPTION_SET_MISSING(set all Y values in the extrapolated range to be missing values),
- OPTION_REPEAT_LAST(use the Y value of the closest input X value for all values in the extrapolated range)
OE_BAD_PARAM (error code: -18): invalid argument of nMode
OE_INT_ARG_LT (error code: -15): invalid argument of nSize of nSrcSize
OE_NOT_STRICTLY_INCREASING (error code: -17): pSrcX[i], i=0,1,...,nSrcSize-1 not strictly increasing
OE_REAL_ARG_LT(error code: -14): invalid dSmoothingFactor
OE_ALLOC_FAIL (error code: -19): memory allocation failed
OE_COEFF_CONV (error code: - 23): the iterative process has failed to converge using method INTERP_TYPE_BSPLINE. Possibly dSmoothingFactor is too small
//Assume that Active worksheet has 4 columns A,B,C and D. Column C and D are x and y data of curve. Column C is in ascending order.
//Column A is x data to be evaluated, interpolation result will be output into column B.
void ocmath_interpolate_ex1(double dd = 1)
int nMode = INTERP_TYPE_BSPLINE;
double dSmoothingFactor = dd;
Worksheet wks = Project.ActiveLayer();
drIn.Add("X", wks, 0, 0, -1, 0);
drIn.Add("X", wks, 0, 1, -1, 1);
drIn.Add("X", wks, 0, 2, -1, 2);
drIn.Add("X", wks, 0, 3, -1, 3);
vector vx, vy, vSrcx, vSrcy;
int nSize = vx.GetSize();
int nSrcSize = vSrcx.GetSize();
int iRet = ocmath_interpolate(vx, vy, nSize, vSrcx, vSrcy, nSrcSize, nMode, dSmoothingFactor);
drIn.SetData(vy, true, 1);//interpolation result
- Interpolation. Three modes are available: Linear, Spline, B-Spline.
- When the mode is B-Spline, if your data, which will be interpolated or extrapolated, is in the interval of the B-Spline, this function calls B-Spline functions of nag to interpolate it, otherwise this function uses the nearest two end points to extend the B-Spline polynomial by linear interpolation.
- cf. Dierckx P: an algorithm for smoothing, differentiation and integration of experimental data using spline functions, J.Comp.Appl.Maths 1 (1975) 165-184.
Header to Include
nag_1d_spline_fit(e02bec)nag_1d_spline_fit(e02bec), Nag Manual