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lgresp_c

Table of contents
Procedure
Abstract
Required_Reading
Keywords
Brief_I/O
Detailed_Input
Detailed_Output
Parameters
Exceptions
Files
Particulars
Examples
Restrictions
Literature_References
Author_and_Institution
Version
Index_Entries

Procedure

   lgresp_c ( Lagrange interpolation on equally spaced points ) 

   SpiceDouble lgresp_c ( SpiceInt            n,
                          SpiceDouble         first,
                          SpiceDouble         step,
                          ConstSpiceDouble    yvals  [],
                          SpiceDouble         x         )

Abstract

   Evaluate a Lagrange interpolating polynomial for a specified
   set of coordinate pairs whose first components are equally
   spaced, at a specified abscissa value.

Required_Reading

   None.

Keywords

   INTERPOLATION
   POLYNOMIAL


Brief_I/O

   VARIABLE  I/O  DESCRIPTION
   --------  ---  --------------------------------------------------
   n          I   Number of points defining the polynomial.
   first      I   First abscissa value.
   step       I   Step size.
   yvals      I   Ordinate values.
   x          I   Point at which to interpolate the polynomial.

   The function returns the value at `x' of the unique polynomial of
   degree n-1 that fits the points in the plane defined by `first',
   `step', and `yvals'.

Detailed_Input

   n           is the number of points defining the polynomial. The
               array `yvals' contains `n' elements.

   first,
   step        are, respectively, a starting abscissa value and a
               step size that define the set of abscissa values
               at which a Lagrange interpolating polynomial is to
               be defined. The set of abscissa values is

                  first   +   i * step,     i = 0, ..., n-1

               `step' must be non-zero.

   yvals       is an array of ordinate values that, together with
               the abscissa values defined by `first' and `step',
               define `n' ordered pairs belonging to the graph of
               a function. The set of points

                  (  first  +  i*step,   yvals(i)  )

               where `i' ranges from 0 to n-1, define the Lagrange
               polynomial used for interpolation.

   x           is the abscissa value at which the interpolating
               polynomial is to be evaluated.

Detailed_Output

   The function returns the value at `x' of the unique polynomial of
   degree n-1 that fits the points in the plane defined by `first',
   `step', and `yvals'.

Parameters

   None.

Exceptions

   1)  If `step' is zero, the error SPICE(INVALIDSTEPSIZE) is signaled
       by a routine in the call tree of this routine. The function
       will return the value 0.0.

   2)  If `n' is less than 1, the error SPICE(INVALIDSIZE) is signaled. The
       function will return the value 0.0.

   3)  This routine does not attempt to ward off or diagnose
       arithmetic overflows.

   4)  If memory cannot be allocated to create the temporary variable
       required for the execution of the underlying Fortran routine,
       the error SPICE(MALLOCFAILED) is signaled. The function
       returns the value result.

Files

   None.

Particulars

   Given a set of `n' distinct abscissa values and corresponding
   ordinate values, there is a unique polynomial of degree n-1,
   often called the "Lagrange polynomial", that fits the graph
   defined by these values. The Lagrange polynomial can be used to
   interpolate the value of a function at a specified point, given a
   discrete set of values of the function.

   Users of this routine must choose the number of points to use
   in their interpolation method. The authors of Reference [1] have
   this to say on the topic:

      Unless there is solid evidence that the interpolating function
      is close in form to the true function F, it is a good idea to
      be cautious about high-order interpolation. We
      enthusiastically endorse interpolations with 3 or 4 points, we
      are perhaps tolerant of 5 or 6; but we rarely go higher than
      that unless there is quite rigorous monitoring of estimated
      errors.

   The same authors offer this warning on the use of the
   interpolating function for extrapolation:

      ...the dangers of extrapolation cannot be overemphasized:
      An interpolating function, which is perforce an extrapolating
      function, will typically go berserk when the argument `x' is
      outside the range of tabulated values by more than the typical
      spacing of tabulated points.

   For Lagrange interpolation on unequally spaced abscissa values,
   see the CSPICE routine lgrint_c.

Examples

   The numerical results shown for these examples may differ across
   platforms. The results depend on the SPICE kernels used as input,
   the compiler and supporting libraries, and the machine specific
   arithmetic implementation.

   1) Fit a cubic polynomial through the points

          ( -1,  -2 )
          (  1,  -8 )
          (  3,  26 )
          (  5, 148 )

      and evaluate this polynomial at x = 2.

      The returned value of lgresp_c should be 1.0, since the
      unique cubic polynomial that fits these points is

                   3      2
         f(x)  =  x  + 2*x  - 4*x - 7


      Example code begins here.


      /.
         Program lgresp_ex1
      ./
      #include <stdio.h>
      #include "SpiceUsr.h"

      int main( )
      {

         SpiceDouble          answer;
         SpiceDouble          first;
         SpiceDouble          step;
         SpiceDouble          yvals  [4];
         SpiceInt             n;

         n         =   4;
         first     =  -1.0;
         step      =   2.0;

         yvals[0]  =  -2.0;
         yvals[1]  =  -8.0;
         yvals[2]  =  26.0;
         yvals[3]  = 148.0;

         answer    =   lgresp_c ( n, first, step, yvals, 2.0 );

         printf( "ANSWER = %f\n", answer );

         return ( 0 );
      }


      When this program was executed on a Mac/Intel/cc/64-bit
      platform, the output was:


      ANSWER = 1.000000


   2) Solve the same problem using a negative step. In order to
      find the solution, set the elements of `yvals' in reverse order.

      The returned value of lgresp_c would still be 1.0.


      Example code begins here.


      /.
         Program lgresp_ex2
      ./
      #include <stdio.h>
      #include "SpiceUsr.h"

      int main( )
      {

         SpiceDouble          answer;
         SpiceDouble          first;
         SpiceDouble          step;
         SpiceDouble          yvals  [4];
         SpiceInt             n;

         n         =   4;
         first     =   5.0;
         step      =  -2.0;

         yvals[0]  = 148.0;
         yvals[1]  =  26.0;
         yvals[2]  =  -8.0;
         yvals[3]  =  -2.0;

         answer    =   lgresp_c ( n, first, step, yvals, 2.0 );

         printf( "ANSWER = %f\n", answer );

         return ( 0 );
      }


      When this program was executed on a Mac/Intel/cc/64-bit
      platform, the output was:


      ANSWER = 1.000000

Restrictions

   None.

Literature_References

   [1]  W. Press, B. Flannery, S. Teukolsky and W. Vetterling,
        "Numerical Recipes -- The Art of Scientific Computing,"
        chapters 3.0 and 3.1, Cambridge University Press, 1986.

Author_and_Institution

   J. Diaz del Rio     (ODC Space)

Version

   -CSPICE Version 1.0.0, 04-AUG-2021 (JDR)

Index_Entries

   interpolate function using Lagrange polynomial
   Lagrange interpolation
Fri Dec 31 18:41:09 2021