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Joined 2026-09-21 Message
Incoming links: Iterator snapshot
The iterator pattern separates traversal state from the aggregate being traversed. A client asks whether another entry exists, then requests that entry, without knowing whether storage is an array, a linked list or another data structure. Distinct iterators have independent positions in a traversal.
In Java, declare
DataList implements Iterable<Point> and provide public Iterator<Point> iterator(). The returned iterator implements hasNext() and next(); exhausted next() throws NoSuchElementException. This also permits an enhanced for (Point p : data) loop.[ref]Java 8 iteration API documentation. Iterable.iterator(), enhanced for support, and Iterator.next() exhaustion contract
Returning
points.iterator() directly would permit removal through that iterator and expose mutable stored Point instances. Part (e) instead returns an unmodifiable iterator snapshot containing fresh Point copies. That choice gives stable traversals and prevents representation exposure, with the tradeoff that a traversal does not see subsequent insertions. ThusFor each sample, include both its marker and its bar. A bar's lower vertical limit is , including negative bars below the horizontal axis. Its horizontal half-width is , rather than . Its marker extends by in both directions. Therefore that sample's axis-aligned bounding box isTaking successive bounding unions includes every sample. Finally unite with to include the stipulated axes. The printed upper-corner formula has one extra closing parenthesis; both the lower-corner formula and the picture confirm the coordinatewise interpretation used here.[ref]
The following commented Java object method may be placed in a graph-view utility software class. It uses
Rect from part (a) and one iterator snapshot from part (e).static Rect barBounds(DataList data, double C, double M) {
if (!Double.isFinite(C) || !Double.isFinite(M) || C <= 0 || M <= 0)
throw new IllegalArgumentException("positive finite margins required");
List<Point> p = new ArrayList<Point>();
for (Point point : data) p.add(point);
int n = p.size();
if (n < 2) throw new IllegalArgumentException("at least two points required");
// This central square supplies the required minimum axis extents.
Rect bounds = new Rect(new Point(-M, -M), new Point(M, M));
for (int i = 0; i < n; ++i) {
double x = p.get(i).getX(), y = p.get(i).getY();
double width;
if (i == 0) {
width = p.get(1).getX() - x;
} else if (i == n - 1) {
width = x - p.get(i - 1).getX();
} else {
width = Math.min(x - p.get(i - 1).getX(),
p.get(i + 1).getX() - x);
}
// Include whichever is wider: marker or half of the bar.
double half = Math.max(C, width / 2.0);
// The bar reaches the baseline; the marker reaches y +/- C.
Rect item = new Rect(new Point(x - half, Math.min(0.0, y - C)),
new Point(x + half, Math.max(0.0, y + C)));
bounds = bounds.Union(item);
}
return bounds;
}This uses the usual assumption that coordinate differences and expanded bounds are representable as finite
double values. Rect rejects overflowed bounds; numerical range extension is not part of the requested geometry. As with all floating-point arithmetic, the calculation approximates the corresponding exact real number formulas.The first matching entry must be retained, and copying an already-started prefix-dropping iterator must not restart the search. Use a private initial buffer together with the underlying iterator snapshot:Before preparation, the iterator still represents the original remaining sequence. During the search, the loop invariant says that every discarded entry fails the predicate, and
class DropUntil[T] private (
p: T => Boolean, iter: Iter[T],
saved: Option[T], alreadyStarted: Boolean) extends Iter[T] {
def this(p: T => Boolean, iter: Iter[T]) =
this(p, iter, None, false)
private var pending: Option[T] = saved
private var started: Boolean = alreadyStarted
private def prepare(): Unit = {
if (!started) {
var found = false
while (!found && iter.hasNext) {
val x = iter.next()
if (p(x)) {
pending = Some(x)
found = true
}
}
started = true
}
}
def hasNext: Boolean = {
prepare()
pending.nonEmpty || iter.hasNext
}
def next(): T = {
prepare()
pending match {
case Some(x) => pending = None; x
case None =>
if (!iter.hasNext) throw new NoSuchElementException("DropUntil.next")
iter.next()
}
}
def copy(): Iter[T] =
new DropUntil[T](p, iter.copy(), pending, started)
}pending is either empty or contains the first satisfying entry just consumed. For a finite input, the number of unread entries is a loop variant. After preparation, the abstract remaining sequence is pending.toList followed by the underlying iterator's remaining sequence. Repeated hasNext calls do not discard or test more entries after the first match.The iterator snapshot copies both the cached entry and the started flag. In particular, copying after the matching entry has been returned continues with the remaining suffix, including later entries that fail
p. Restarting new DropUntil(p, iter.copy()) at that point would wrongly drop another prefix.As usual, assume a deterministic predicate without shared mutable effects. On an infinite input having no match, the first demand cannot terminate: no finite inspection establishes absence. Independence here concerns cursor state; arbitrary mutation of shared element objects is outside the iterator contract.Keep a buffered first match and a flag recording whether the initial prefix still needs to be skipped:
class DropUntil[T] private (
p: T => Boolean,
iter: Iter[T],
private var cached: Option[T],
private var seeking: Boolean) extends Iter[T] {
def this(p: T => Boolean, iter: Iter[T]) =
this(p, iter, None, true)
private def prepare(): Unit = {
if (seeking) {
while (cached.isEmpty && iter.hasNext) {
val x = iter.next()
if (p(x)) cached = Some(x)
}
seeking = false
}
}
def hasNext: Boolean = {
prepare()
cached.nonEmpty || iter.hasNext
}
def next(): T = {
prepare()
cached match {
case Some(x) => cached = None; x
case None =>
if (!iter.hasNext) throw new NoSuchElementException("DropUntil.next")
iter.next()
}
}
def copy(): Iter[T] = {
prepare()
new DropUntil[T](p, iter.copy(), cached, false)
}
}While seeking,
prepare drops exactly the rejected prefix and caches the first accepted value, including a possible null payload as Some(null). Afterwards the abstract remainder is the cache, if any, followed by the underlying remainder; later values are returned even when they fail p. Repeated hasNext calls do not lose the cached value.The iterator snapshot copies the underlying cursor and the cached value, then marks the initial search complete. It does not reconstruct a fresh two-argument
DropUntil, which could incorrectly discard later values. Resolving the initial search before copying also avoids having two snapshots independently rerun a privately stateful predicate. The wrapper owns consumption of the supplied source cursor. If that source is infinite and never produces an accepted value, seeking cannot finish. This is a prefix-dropping iterator, rather than a repeatedly demand-driven filtering iterator. Prefix-dropping iterator 2026-10-31
Discard input values until the first one satisfying a predicate, then return that value and every remaining value without testing the predicate again. A demand-driven filtering iterator instead keeps testing and can discard later values too. A buffered first match must survive repeated availability tests and iterator snapshots. A flag distinguishes the initial seeking phase from the already-positioned remainder.