cumIntegration function

Array cumIntegration(Array y, { Array? x, int dx = 1, double? initial, })

Compute the numerical accumulative integration of an Array using the trapezoidal rule.

• y : input array to integrate
• x : The sample points corresponding to the y values. If x is null, the sample points are assumed to be evenly spaced dx apart. The default is null.
• dx : The spacing between sample points when x is None. The default is 1.
• initial : optional. If given, uses this value as the first value in the returned result. Typically this value should be 0. Default is null, which means no value at x0 is returned and return has one element less than y along the axis of integration.

References

1. "doc scipy.integrate.cumtrapz". https://docs.scipy.org/doc/scipy-0.18.1/reference/generated/scipy.integrate.cumtrapz.html. Retrieved 2019-08-01.
2. "scipy.integrate.cumtrapz". https://github.com/scipy/scipy/blob/v0.18.1/scipy/integrate/quadrature.py#L206-L295. Retrieved 2019-08-01.

Examples

var y = Array([1, 2, 3]);

print(cumIntegration(y));

Implementation

Array cumIntegration(Array y, {Array? x, int dx = 1, double? initial}) {
  checkParamsGetRangeArray(y, x, dx);

  var d;
  if (x != null) {
    d = arrayDiff(x);
  } else {
    d = Array.fixed(y.length - 1, initialValue: dx.toDouble());
  }

  var slice1 = y.getRangeArray(0, y.length - 1);
  var slice2 = y.getRangeArray(1, y.length);

  var ret = arrayCumSum(d * arrayDivisionToScalar(slice1 + slice2, 2.0));

  if (initial != null) {
    ret = arrayConcat([arrayMultiplyToScalar(ones(1), initial), ret]);
  }

  return ret;
}