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-rw-r--r--bin/ai/library/queue/binary_heap/library.nut12
-rw-r--r--bin/ai/library/queue/binary_heap/main.nut131
-rw-r--r--bin/ai/library/queue/fibonacci_heap/library.nut12
-rw-r--r--bin/ai/library/queue/fibonacci_heap/main.nut204
-rw-r--r--bin/ai/library/queue/priority_queue/library.nut12
-rw-r--r--bin/ai/library/queue/priority_queue/main.nut115
6 files changed, 486 insertions, 0 deletions
diff --git a/bin/ai/library/queue/binary_heap/library.nut b/bin/ai/library/queue/binary_heap/library.nut
new file mode 100644
index 000000000..3a96617a9
--- /dev/null
+++ b/bin/ai/library/queue/binary_heap/library.nut
@@ -0,0 +1,12 @@
+/* $Id$ */
+
+class BinaryHeap extends AILibrary {
+ function GetAuthor() { return "OpenTTD NoAI Developers Team"; }
+ function GetName() { return "Binary Heap"; }
+ function GetDescription() { return "An implementation of a Binary Heap"; }
+ function GetVersion() { return 1; }
+ function GetDate() { return "2008-06-10"; }
+ function CreateInstance() { return "BinaryHeap"; }
+}
+
+RegisterLibrary(BinaryHeap());
diff --git a/bin/ai/library/queue/binary_heap/main.nut b/bin/ai/library/queue/binary_heap/main.nut
new file mode 100644
index 000000000..1bbb3914f
--- /dev/null
+++ b/bin/ai/library/queue/binary_heap/main.nut
@@ -0,0 +1,131 @@
+/* $Id$ */
+
+/**
+ * Binary Heap.
+ * Peek and Pop always return the current lowest value in the list.
+ * Sort is done on insertion and on deletion.
+ */
+class BinaryHeap
+{
+ _queue = null;
+ _count = 0;
+
+ constructor()
+ {
+ _queue = [];
+ }
+
+ /**
+ * Insert a new entry in the list.
+ * The complexity of this operation is O(ln n).
+ * @param item The item to add to the list.
+ * @param priority The priority this item has.
+ */
+ function Insert(item, priority);
+
+ /**
+ * Pop the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(ln n).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Pop();
+
+ /**
+ * Peek the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(1).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Peek();
+
+ /**
+ * Get the amount of current items in the list.
+ * The complexity of this operation is O(1).
+ * @return The amount of items currently in the list.
+ */
+ function Count();
+
+ /**
+ * Check if an item exists in the list.
+ * The complexity of this operation is O(n).
+ * @param item The item to check for.
+ * @return True if the item is already in the list.
+ */
+ function Exists(item);
+};
+
+function BinaryHeap::Insert(item, priority)
+{
+ /* Append dummy entry */
+ _queue.append(0);
+ _count++;
+
+ local hole;
+ /* Find the point of insertion */
+ for (hole = _count - 1; hole > 0 && priority <= _queue[hole / 2][1]; hole /= 2)
+ _queue[hole] = _queue[hole / 2];
+ /* Insert new pair */
+ _queue[hole] = [item, priority];
+
+ return true;
+}
+
+function BinaryHeap::Pop()
+{
+ if (_count == 0) return null;
+
+ local node = _queue[0];
+ /* Remove the item from the list by putting the last value on top */
+ _queue[0] = _queue[_count - 1];
+ _queue.pop();
+ _count--;
+ /* Bubble down the last value to correct the tree again */
+ _BubbleDown();
+
+ return node[0];
+}
+
+function BinaryHeap::Peek()
+{
+ if (_count == 0) return null;
+
+ return _queue[0][0];
+}
+
+function BinaryHeap::Count()
+{
+ return _count;
+}
+
+function BinaryHeap::Exists(item)
+{
+ /* Brute-force find the item (there is no faster way, as we don't have the priority number) */
+ foreach (node in _queue) {
+ if (node[0] == item) return true;
+ }
+
+ return false;
+}
+
+
+
+function BinaryHeap::_BubbleDown()
+{
+ if (_count == 0) return;
+
+ local hole = 1;
+ local tmp = _queue[0];
+
+ /* Start switching parent and child until the tree is restored */
+ while (hole * 2 < _count + 1) {
+ local child = hole * 2;
+ if (child != _count && _queue[child][1] <= _queue[child - 1][1]) child++;
+ if (_queue[child - 1][1] > tmp[1]) break;
+
+ _queue[hole - 1] = _queue[child - 1];
+ hole = child;
+ }
+ /* The top value is now at his new place */
+ _queue[hole - 1] = tmp;
+}
diff --git a/bin/ai/library/queue/fibonacci_heap/library.nut b/bin/ai/library/queue/fibonacci_heap/library.nut
new file mode 100644
index 000000000..1ea7260e0
--- /dev/null
+++ b/bin/ai/library/queue/fibonacci_heap/library.nut
@@ -0,0 +1,12 @@
+/* $Id$ */
+
+class FibonacciHeap extends AILibrary {
+ function GetAuthor() { return "OpenTTD NoAI Developers Team"; }
+ function GetName() { return "Fibonacci Heap"; }
+ function GetDescription() { return "An implementation of a Fibonacci Heap"; }
+ function GetVersion() { return 1; }
+ function GetDate() { return "2008-08-22"; }
+ function CreateInstance() { return "FibonacciHeap"; }
+}
+
+RegisterLibrary(FibonacciHeap());
diff --git a/bin/ai/library/queue/fibonacci_heap/main.nut b/bin/ai/library/queue/fibonacci_heap/main.nut
new file mode 100644
index 000000000..7c6b3ece2
--- /dev/null
+++ b/bin/ai/library/queue/fibonacci_heap/main.nut
@@ -0,0 +1,204 @@
+/* $Id$ */
+
+/**
+ * Fibonacci heap.
+ * This heap is heavily optimized for the Insert and Pop functions.
+ * Peek and Pop always return the current lowest value in the list.
+ * Insert is implemented as a lazy insert, as it will simply add the new
+ * node to the root list. Sort is done on every Pop operation.
+ */
+class FibonacciHeap {
+ _min = null;
+ _min_index = 0;
+ _min_priority = 0;
+ _count = 0;
+ _root_list = null;
+
+ /**
+ * Create a new fibonacci heap.
+ * http://en.wikipedia.org/wiki/Fibonacci_heap
+ */
+ constructor() {
+ _count = 0;
+ _min = Node();
+ _min.priority = 0x7FFFFFFF;
+ _min_index = 0;
+ _min_priority = 0x7FFFFFFF;
+ _root_list = [];
+ }
+
+ /**
+ * Insert a new entry in the heap.
+ * The complexity of this operation is O(1).
+ * @param item The item to add to the list.
+ * @param priority The priority this item has.
+ */
+ function Insert(item, priority);
+
+ /**
+ * Pop the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(ln n).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Pop();
+
+ /**
+ * Peek the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(1).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Peek();
+
+ /**
+ * Get the amount of current items in the list.
+ * The complexity of this operation is O(1).
+ * @return The amount of items currently in the list.
+ */
+ function Count();
+
+ /**
+ * Check if an item exists in the list.
+ * The complexity of this operation is O(n).
+ * @param item The item to check for.
+ * @return True if the item is already in the list.
+ */
+ function Exists(item);
+};
+
+function FibonacciHeap::Insert(item, priority) {
+ /* Create a new node instance to add to the heap. */
+ local node = Node();
+ /* Changing params is faster than using constructor values */
+ node.item = item;
+ node.priority = priority;
+
+ /* Update the reference to the minimum node if this node has a
+ * smaller priority. */
+ if (_min_priority > priority) {
+ _min = node;
+ _min_index = _root_list.len();
+ _min_priority = priority;
+ }
+
+ _root_list.append(node);
+ _count++;
+}
+
+function FibonacciHeap::Pop() {
+
+ if (_count == 0) return null;
+
+ /* Bring variables from the class scope to this scope explicitly to
+ * optimize variable lookups by Squirrel. */
+ local z = _min;
+ local tmp_root_list = _root_list;
+
+ /* If there are any children, bring them all to the root level. */
+ tmp_root_list.extend(z.child);
+
+ /* Remove the minimum node from the rootList. */
+ tmp_root_list.remove(_min_index);
+ local root_cache = {};
+
+ /* Now we decrease the number of nodes on the root level by
+ * merging nodes which have the same degree. The node with
+ * the lowest priority value will become the parent. */
+ foreach(x in tmp_root_list) {
+ local y;
+
+ /* See if we encountered a node with the same degree already. */
+ while (y = root_cache.rawdelete(x.degree)) {
+ /* Check the priorities. */
+ if (x.priority > y.priority) {
+ local tmp = x;
+ x = y;
+ y = tmp;
+ }
+
+ /* Make y a child of x. */
+ x.child.append(y);
+ x.degree++;
+ }
+
+ root_cache[x.degree] <- x;
+ }
+
+ /* The root_cache contains all the nodes which will form the
+ * new rootList. We reset the priority to the maximum number
+ * for a 32 signed integer to find a new minumum. */
+ tmp_root_list.resize(root_cache.len());
+ local i = 0;
+ local tmp_min_priority = 0x7FFFFFFF;
+
+ /* Now we need to find the new minimum among the root nodes. */
+ foreach (val in root_cache) {
+ if (val.priority < tmp_min_priority) {
+ _min = val;
+ _min_index = i;
+ tmp_min_priority = val.priority;
+ }
+
+ tmp_root_list[i++] = val;
+ }
+
+ /* Update global variables. */
+ _min_priority = tmp_min_priority;
+
+ _count--;
+ return z.item;
+}
+
+function FibonacciHeap::Peek() {
+ if (_count == 0) return null;
+ return _min.item;
+}
+
+function FibonacciHeap::Count() {
+ return _count;
+}
+
+function FibonacciHeap::Exists(item) {
+ return ExistsIn(_root_list, item);
+}
+
+/**
+ * Auxilary function to search through the whole heap.
+ * @param list The list of nodes to look through.
+ * @param item The item to search for.
+ * @return True if the item is found, false otherwise.
+ */
+function FibonacciHeap::ExistsIn(list, item) {
+
+ foreach (val in list) {
+ if (val.item == item) {
+ return true;
+ }
+
+ foreach (c in val.child) {
+ if (ExistsIn(c, item)) {
+ return true;
+ }
+ }
+ }
+
+ /* No luck, item doesn't exists in the tree rooted under list. */
+ return false;
+}
+
+/**
+ * Basic class the fibonacci heap is composed of.
+ */
+class FibonacciHeap.Node {
+ degree = null;
+ child = null;
+
+ item = null;
+ priority = null;
+
+ constructor() {
+ child = [];
+ degree = 0;
+ }
+};
diff --git a/bin/ai/library/queue/priority_queue/library.nut b/bin/ai/library/queue/priority_queue/library.nut
new file mode 100644
index 000000000..a8c615ed1
--- /dev/null
+++ b/bin/ai/library/queue/priority_queue/library.nut
@@ -0,0 +1,12 @@
+/* $Id$ */
+
+class PriorityQueue extends AILibrary {
+ function GetAuthor() { return "OpenTTD NoAI Developers Team"; }
+ function GetName() { return "Priority Queue"; }
+ function GetDescription() { return "An implementation of a Priority Queue"; }
+ function GetVersion() { return 2; }
+ function GetDate() { return "2008-06-10"; }
+ function CreateInstance() { return "PriorityQueue"; }
+}
+
+RegisterLibrary(PriorityQueue());
diff --git a/bin/ai/library/queue/priority_queue/main.nut b/bin/ai/library/queue/priority_queue/main.nut
new file mode 100644
index 000000000..bafc93ac5
--- /dev/null
+++ b/bin/ai/library/queue/priority_queue/main.nut
@@ -0,0 +1,115 @@
+/* $Id$ */
+
+/**
+ * Priority Queue.
+ * Peek and Pop always return the current lowest value in the list.
+ * Sort is done on insertion only.
+ */
+class PriorityQueue
+{
+ _queue = null;
+ _count = 0;
+
+ constructor()
+ {
+ _count = 0;
+ _queue = [];
+ }
+
+ /**
+ * Insert a new entry in the list.
+ * The complexity of this operation is O(n).
+ * @param item The item to add to the list.
+ * @param priority The priority this item has.
+ */
+ function Insert(item, priority);
+
+ /**
+ * Pop the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(1).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Pop();
+
+ /**
+ * Peek the first entry of the list.
+ * This is always the item with the lowest priority.
+ * The complexity of this operation is O(1).
+ * @return The item of the entry with the lowest priority.
+ */
+ function Peek();
+
+ /**
+ * Get the amount of current items in the list.
+ * The complexity of this operation is O(1).
+ * @return The amount of items currently in the list.
+ */
+ function Count();
+
+ /**
+ * Check if an item exists in the list.
+ * The complexity of this operation is O(n).
+ * @param item The item to check for.
+ * @return True if the item is already in the list.
+ */
+ function Exists(item);
+};
+
+function PriorityQueue::Insert(item, priority)
+{
+ /* Append dummy entry */
+ _queue.append(0);
+ _count++;
+
+ local i;
+ /* Find the point of insertion */
+ for (i = _count - 2; i >= 0; i--) {
+ if (priority > _queue[i][1]) {
+ /* All items bigger move one place to the right */
+ _queue[i + 1] = _queue[i];
+ } else if (item == _queue[i][0]) {
+ /* Same item, ignore insertion */
+ return false;
+ } else {
+ /* Found place to insert at */
+ break;
+ }
+ }
+ /* Insert new pair */
+ _queue[i + 1] = [item, priority];
+
+ return true;
+}
+
+function PriorityQueue::Pop()
+{
+ if (_count == 0) return null;
+
+ local node = _queue.pop();
+ _count--;
+
+ return node[0];
+}
+
+function PriorityQueue::Peek()
+{
+ if (_count == 0) return null;
+
+ return _queue[_count - 1][0];
+}
+
+function PriorityQueue::Count()
+{
+ return _count;
+}
+
+function PriorityQueue::Exists(item)
+{
+ /* Brute-force find the item (there is no faster way, as we don't have the priority number) */
+ foreach (node in _queue) {
+ if (node[0] == item) return true;
+ }
+
+ return false;
+}