exponentialIntegral function

double exponentialIntegral (double x, int n)

Computes the generalized Exponential Integral function (En).

This implementation of the computation of the Exponential Integral function follows the derivation in "Handbook of Mathematical Functions, Applied Mathematics Series, Volume 55", Abramowitz, M., and Stegun, I.A. 1964, reprinted 1968 by Dover Publications, New York), Chapters 6, 7, and 26. AND "Advanced mathematical methods for scientists and engineers", Bender, Carl M.; Steven A. Orszag (1978). page 253

for x > 1 uses continued fraction approach that is often used to compute incomplete gamma. for 0 < x <= 1 uses Taylor series expansion

Our unit tests suggest that the accuracy of the Exponential Integral function is correct up to 13 floating point digits.

Implementation

``````double exponentialIntegral(double x, int n) {
//parameter validation
if (n < 0 || x < 0.0) {
throw ArgumentError("x and n must be positive: x=\${x}, n=\${n}");
}

const double epsilon = 0.00000000000000001;
int maxIterations = 100;
int i, ii;
double ndbl = n.toDouble();
double result;
double nearDoubleMin =
1e-100; //needs a very small value that is not quite as small as the lowest value double can take
double factorial = 1.0;
double del;
double psi;
double a, b, c, d, h; //variables for continued fraction

//special cases
if (n == 0) {
return exp(-1.0 * x) / x;
} else if (x == 0.0) {
return 1.0 / (ndbl - 1.0);
}
//general cases
//continued fraction for large x
if (x > 1.0) {
b = x + n.toDouble();
c = 1.0 / nearDoubleMin;
d = 1.0 / b;
h = d;
for (i = 1; i <= maxIterations; i++) {
a = -1.0 * i.toDouble() * ((ndbl - 1.0) + i.toDouble());
b += 2.0;
d = 1.0 / (a * d + b);
c = b + a / c;
del = c * d;
h = h * del;
if ((del - 1.0).abs() < epsilon) {
return h * exp(-x);
}
}

throw ArgumentError(
"continued fraction failed to converge for x=\${x}, n=\${n})");
} else {
//series computation for small x
result = ((ndbl - 1.0) != 0
? 1.0 / (ndbl - 1.0)
: (-1.0 * log(x) - eulerMascheroni)); //Set first term.
for (i = 1; i <= maxIterations; i++) {
factorial *= (-1.0 * x / (i.toDouble()));
if (i != (ndbl - 1.0)) {
del = -factorial / (i - (ndbl - 1.0));
} else {
psi = -1.0 * eulerMascheroni;
for (ii = 1; ii <= (ndbl - 1.0); ii++) {
psi += (1.0 / ii.toDouble());
}
del = factorial * (-1.0 * log(x) + psi);
}
result += del;
if (del.abs() < result.abs() * epsilon) {
return result;
}
}

throw ArgumentError("series failed to converge for x=\${x}, n=\${n})");
}
}``````