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NAG Toolbox: nag_specfun_fresnel_c (s20ad)

 Contents

    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example

Purpose

nag_specfun_fresnel_c (s20ad) returns a value for the Fresnel integral Cx, via the function name.

Syntax

[result, ifail] = s20ad(x)
[result, ifail] = nag_specfun_fresnel_c(x)

Description

nag_specfun_fresnel_c (s20ad) evaluates an approximation to the Fresnel integral
Cx=0xcosπ2t2dt.  
Note:  Cx=-C-x, so the approximation need only consider x0.0.
The function is based on three Chebyshev expansions:
For 0<x3,
Cx=xr=0arTrt,   with ​ t=2 x3 4-1.  
For x>3,
Cx=12+fxxsinπ2x2-gxx3cosπ2x2 ,  
where fx=r=0brTrt,
and gx=r=0crTrt,
with t=2 3x 4-1.
For small x, Cxx. This approximation is used when x is sufficiently small for the result to be correct to machine precision.
For large x, fx 1π  and gx 1π2 . Therefore for moderately large x, when 1π2x3  is negligible compared with 12 , the second term in the approximation for x>3 may be dropped. For very large x, when 1πx  becomes negligible, Cx 12 . However there will be considerable difficulties in calculating sin π2x2 accurately before this final limiting value can be used. Since sin π2x2 is periodic, its value is essentially determined by the fractional part of x2. If x2=N+θ, where N is an integer and 0θ<1, then sin π2x2 depends on θ and on N modulo 4. By exploiting this fact, it is possible to retain some significance in the calculation of sin π2x2 either all the way to the very large x limit, or at least until the integer part of x2  is equal to the maximum integer allowed on the machine.

References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications

Parameters

Compulsory Input Parameters

1:     x – double scalar
The argument x of the function.

Optional Input Parameters

None.

Output Parameters

1:     result – double scalar
The result of the function.
2:     ifail int64int32nag_int scalar
ifail=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

There are no failure exits from nag_specfun_fresnel_c (s20ad). The argument ifail has been included for consistency with other functions in this chapter.

Accuracy

Let δ and ε be the relative errors in the argument and result respectively.
If δ is somewhat larger than the machine precision (i.e if δ is due to data errors etc.), then ε and δ are approximately related by:
ε x cos π2 x2 Cx δ.  
Figure 1 shows the behaviour of the error amplification factor x cos π2 x2 Cx .
However, if δ is of the same order as the machine precision, then rounding errors could make ε slightly larger than the above relation predicts.
For small x, εδ and there is no amplification of relative error.
For moderately large values of x,
ε 2x cos π2 x2 δ  
and the result will be subject to increasingly large amplification of errors. However the above relation breaks down for large values of x (i.e., when 1x2  is of the order of the machine precision); in this region the relative error in the result is essentially bounded by 2πx .
Hence the effects of error amplification are limited and at worst the relative error loss should not exceed half the possible number of significant figures.
Figure 1
Figure 1

Further Comments

None.

Example

This example reads values of the argument x from a file, evaluates the function at each value of x and prints the results.
function s20ad_example


fprintf('s20ad example results\n\n');

x = [0   0.5   1   2   4   5   6   8   10   -1   1000];
n = size(x,2);
result = x;

for j=1:n
  [result(j), ifail] = s20ad(x(j));
end

disp('      x          C(x)');
fprintf('%12.3e%12.3e\n',[x; result]);

s20ad_plot;



function s20ad_plot
  x = [-10:0.02:10];
  for j = 1:numel(x)
    [C(j), ifail] = s20ad(x(j));
  end

  fig1 = figure;
  plot(x,C,'-r');
  xlabel('x');
  ylabel('C(x)');
  title('Fresnel Integral C(x)');

s20ad example results

      x          C(x)
   0.000e+00   0.000e+00
   5.000e-01   4.923e-01
   1.000e+00   7.799e-01
   2.000e+00   4.883e-01
   4.000e+00   4.984e-01
   5.000e+00   5.636e-01
   6.000e+00   4.995e-01
   8.000e+00   4.998e-01
   1.000e+01   4.999e-01
  -1.000e+00  -7.799e-01
   1.000e+03   5.000e-01
s20ad_fig1.png

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