CSHER

Computes the Hermite cubic spline interpolant.

Required Arguments

XDATA — Array of length NDATA containing the data point abscissas.   (Input)
The data point abscissas must be distinct.

FDATA — Array of length NDATA containing the data point ordinates.   (Input)

DFDATA — Array of length NDATA containing the values of the derivative.   (Input)

BREAK — Array of length NDATA containing the breakpoints for the piecewise cubic representation.   (Output)

CSCOEF — Matrix of size 4 by NDATA containing the local coefficients of the cubic pieces.   (Output)

Optional Arguments

NDATA — Number of data points.   (Input)
Default: NDATA = size (XDATA,1).

FORTRAN 90 Interface

Generic:          CALL CSHER (XDATA, FDATA, DFDATA, BREAK, CSCOEF [,…])

Specific:         The specific interface names are S_CSHER and D_CSHER.

FORTRAN 77 Interface

Single:            CALL CSHER (NDATA, XDATA, FDATA, BREAK, CSCOEF)

Double:          The double precision name is DCSHER.

Description

The routine CSHER computes a C 1 cubic spline interpolant to the set of data points

for i = 1, , NDATA = N. The breakpoints of the spline are the abscissas.

If the data points arise from the values of a smooth (say C 4) function f, i.e.,

then the error will behave in a predictable fashion. Let ξ be the

breakpoint vector for the above spline interpolant. Then, the maximum absolute error satisfies

where

For more details, see de Boor (1978, page 51).

Comments

1.         Workspace may be explicitly provided, if desired, by use of C2HER/DC2HER. The reference is:

CALL C2HER (NDATA, XDATA, FDATA, DFDATA, BREAK, CSCOEF, IWK)

The additional argument is:

IWK — Work array of length NDATA.

2.         Informational error

Type   Code

4           2                  The XDATA values must be distinct.

3.         The cubic spline can be evaluated using CSVAL; its derivative can be evaluated using CSDER.

4.         Note that column NDATA of CSCOEF is used as workspace.

Example

In this example, a cubic spline interpolant to a function f is computed. The value of the function f and its derivative f ʹ are computed on the interpolation nodes and passed to CSHER. The values of this spline are then compared with the exact function values.

 

      USE CSHER_INT

      USE UMACH_INT

      USE CSVAL_INT

 

      IMPLICIT   NONE

      INTEGER    NDATA

      PARAMETER  (NDATA=11)

!

      INTEGER    I, NINTV, NOUT

      REAL       BREAK(NDATA), COS, CSCOEF(4,NDATA), DF,&

                 DFDATA(NDATA), F, FDATA(NDATA), FLOAT, SIN, X,&

                 XDATA(NDATA)

      INTRINSIC  COS, FLOAT, SIN

!                                  Define function and derivative

      F(X)  = SIN(15.0*X)

      DF(X) = 15.0*COS(15.0*X)

!                                  Set up a grid

      DO 10  I=1, NDATA

         XDATA(I)  = FLOAT(I-1)/FLOAT(NDATA-1)

         FDATA(I)  = F(XDATA(I))

         DFDATA(I) = DF(XDATA(I))

   10 CONTINUE

!                                  Compute cubic spline interpolant

      CALL CSHER (XDATA, FDATA, DFDATA, BREAK, CSCOEF)

!                                  Get output unit number

      CALL UMACH (2, NOUT)

!                                  Write heading

      WRITE (NOUT,99999)

99999 FORMAT (13X, 'X', 9X, 'Interpolant', 5X, 'Error')

      NINTV = NDATA - 1

!                                  Print the interpolant on a finer grid

      DO 20  I=1, 2*NDATA - 1

         X = FLOAT(I-1)/FLOAT(2*NDATA-2)

         WRITE (NOUT,'(2F15.3, F15.6)') X, CSVAL(X,BREAK,CSCOEF)&

                                      , F(X) - CSVAL(X,BREAK,&

                                      CSCOEF)

 

   20 CONTINUE

      END

Output

 

   X         Interpolant     Error
0.000          0.000       0.000000
0.050          0.673       0.008654
0.100          0.997       0.000000
0.150          0.768       0.009879
0.200          0.141       0.000000
0.250         -0.564      -0.007257
0.300         -0.978       0.000000
0.350         -0.848      -0.010906
0.400         -0.279       0.000000
0.450          0.444       0.005714
0.500          0.938       0.000000
0.550          0.911       0.011714
0.600          0.412       0.000000
0.650         -0.315      -0.004057
0.700         -0.880       0.000000
0.750         -0.956      -0.012288
0.800         -0.537       0.000000
0.850          0.180       0.002318
0.900          0.804       0.000000
0.950          0.981       0.012616
1.000          0.650       0.000000


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