WPF ObservableCollection – Add millions of data within milliseconds
Adding huge amount of Data to an ObservableCollection can cause GUI freezes. Even if operating on another thread, the process of adding items is pretty slow. But why?
WPF Scrollable + Zoomable + Dragable Control
Unluckily there is no standard control to zoom, drag and scroll your content. My implementation is based on following tutorial. With this implementation you are able to zoom, drag and scroll arbitrary controls. Showcase ScrollDragZoomControl.xaml
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<UserControl x:Class="MinimalMonitoringClient.Controls.ScrollDragZoomControl" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" Background="Transparent"> <UserControl.Template> <ControlTemplate TargetType="UserControl"> <ScrollViewer x:Name="scrollViewer" Loaded="scrollViewer_Loaded" HorizontalScrollBarVisibility="Visible" VerticalScrollBarVisibility="Visible"> <Grid Name="grid" RenderTransformOrigin="0.5,0.5"> <Grid.LayoutTransform> <TransformGroup> <ScaleTransform x:Name="scaleTransform" /> </TransformGroup> </Grid.LayoutTransform> <Viewbox> <!-- Present the actual stuff the user wants to display --> <ContentPresenter /> </Viewbox> </Grid> </ScrollViewer> </ControlTemplate> </UserControl.Template> </UserControl> |
ScrollDragZoomControl.xaml.cs
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using System.Windows; using System.Windows.Controls; using System.Windows.Input; using System.Windows.Media; namespace NAMESPACE { /// <summary> /// Interaktionslogik für ScrollDragZoomControl.xaml /// </summary> public partial class ScrollDragZoomControl : UserControl { private int zoomLevel = 1; private ScaleTransform scaleTransform; private ScrollViewer scrollViewer; private Grid grid; Point? lastCenterPositionOnTarget; Point? lastMousePositionOnTarget; Point? lastDragPoint; public ScrollDragZoomControl() { InitializeComponent(); } private void scrollViewer_Loaded(object sender, RoutedEventArgs e) { scaleTransform = (ScaleTransform)Template.FindName("scaleTransform", this); scrollViewer = (ScrollViewer)Template.FindName("scrollViewer", this); grid = (Grid)Template.FindName("grid", this); scrollViewer.ScrollChanged += OnScrollViewerScrollChanged; scrollViewer.MouseLeftButtonUp += OnMouseLeftButtonUp; scrollViewer.PreviewMouseLeftButtonUp += OnMouseLeftButtonUp; scrollViewer.PreviewMouseWheel += OnPreviewMouseWheel; scrollViewer.PreviewMouseLeftButtonDown += OnMouseLeftButtonDown; scrollViewer.MouseMove += OnMouseMove; } void OnMouseMove(object sender, MouseEventArgs e) { if (lastDragPoint.HasValue) { Point posNow = e.GetPosition(scrollViewer); double dX = posNow.X - lastDragPoint.Value.X; double dY = posNow.Y - lastDragPoint.Value.Y; lastDragPoint = posNow; scrollViewer.ScrollToHorizontalOffset(scrollViewer.HorizontalOffset - dX); scrollViewer.ScrollToVerticalOffset(scrollViewer.VerticalOffset - dY); } } void OnMouseLeftButtonDown(object sender, MouseButtonEventArgs e) { var mousePos = e.GetPosition(scrollViewer); if (mousePos.X <= scrollViewer.ViewportWidth && mousePos.Y < scrollViewer.ViewportHeight) //make sure we still can use the scrollbars { scrollViewer.Cursor = Cursors.SizeAll; lastDragPoint = mousePos; Mouse.Capture(scrollViewer); } } void OnPreviewMouseWheel(object sender, MouseWheelEventArgs e) { lastMousePositionOnTarget = Mouse.GetPosition(grid); if (e.Delta > 0) zoomLevel++; else if (e.Delta < 0) zoomLevel--; zoomLevel = zoomLevel < 1 ? 1 : zoomLevel; scaleTransform.ScaleX = zoomLevel; scaleTransform.ScaleY = zoomLevel; var centerOfViewport = new Point(scrollViewer.ViewportWidth / 2, scrollViewer.ViewportHeight / 2); lastCenterPositionOnTarget = scrollViewer.TranslatePoint(centerOfViewport, grid); e.Handled = true; } void OnMouseLeftButtonUp(object sender, MouseButtonEventArgs e) { scrollViewer.Cursor = Cursors.Arrow; scrollViewer.ReleaseMouseCapture(); lastDragPoint = null; } void OnScrollViewerScrollChanged(object sender, ScrollChangedEventArgs e) { if (e.ExtentHeightChange != 0 || e.ExtentWidthChange != 0) { Point? targetBefore = null; Point? targetNow = null; if (!lastMousePositionOnTarget.HasValue) { if (lastCenterPositionOnTarget.HasValue) { var centerOfViewport = new Point(scrollViewer.ViewportWidth / 2, scrollViewer.ViewportHeight / 2); Point centerOfTargetNow = scrollViewer.TranslatePoint(centerOfViewport, grid); targetBefore = lastCenterPositionOnTarget; targetNow = centerOfTargetNow; } } else { targetBefore = lastMousePositionOnTarget; targetNow = Mouse.GetPosition(grid); lastMousePositionOnTarget = null; } if (targetBefore.HasValue) { double dXInTargetPixels = targetNow.Value.X - targetBefore.Value.X; double dYInTargetPixels = targetNow.Value.Y - targetBefore.Value.Y; double multiplicatorX = e.ExtentWidth / grid.Width; double multiplicatorY = e.ExtentHeight / grid.Height; double newOffsetX = scrollViewer.HorizontalOffset - dXInTargetPixels * multiplicatorX; double newOffsetY = scrollViewer.VerticalOffset - dYInTargetPixels * multiplicatorY; if (double.IsNaN(newOffsetX) || double.IsNaN(newOffsetY)) { return; } scrollViewer.ScrollToHorizontalOffset(newOffsetX); scrollViewer.ScrollToVerticalOffset(newOffsetY); } } } } } |
Usage Add the „ScrollDragZoomControl“ to your project and use it as follows:
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<controls:ScrollDragZoomControl> <!-- Your Content to present --> </controls:ScrollDragZoomControl> |
ABP – Alpha-Beta Pruning
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private BiPredicate<Integer, Node> searchLimitingPredicate; private int depth; public AlphaBetaSearch(BiPredicate<Integer, Node> searchLimitingPredicate) { this.searchLimitingPredicate = searchLimitingPredicate; } public Pair<Node, Double> search(Node start, Function<Node, Double> evalFunction) { Node winner = start; double value = Double.NEGATIVE_INFINITY; double alpha = Double.NEGATIVE_INFINITY; double beta = Double.POSITIVE_INFINITY; for (Node n : start.adjacent()) { double temp = min(n, evalFunction, alpha, beta); if (temp > value) { value = temp; winner = n; } depth = 0; } return new Pair<Node, Double>(winner, value); } private double min(Node node, Function<Node, Double> evalFunction, double alpha, double beta) { if (node.isLeaf() || !searchLimitingPredicate.test(depth+1, node)) { return evalFunction.apply(node); } depth++; double value = Double.POSITIVE_INFINITY; for (Node n : node.adjacent()) { value = Math.min(value, max(n, evalFunction, alpha, beta)); if (value <= alpha) break; beta = Math.min(beta, value); } depth--; return value; } private double max(Node node, Function<Node, Double> evalFunction, double alpha, double beta) { if (node.isLeaf() || !searchLimitingPredicate.test(depth+1, node)) { return evalFunction.apply(node); } depth++; double value = Double.NEGATIVE_INFINITY; for (Node n : node.adjacent()) { value = Math.max(value, min(n, evalFunction, alpha, beta)); if (value >= beta) break; alpha = Math.max(alpha, value); } depth--; return value; } |
DLS – Depth-Limited Search
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private StackWithFastContains<Node> path; private int limit; public DLDFS(int limit) { this.limit = limit; } public Node search(Node start, Predicate<Node> endPredicate) { //Initial the stackWithFastContains path = new StackWithFastContains<>(); return searchForNode(start, endPredicate, limit); } private Node searchForNode(Node currentNode, Predicate<Node> toSearchFor, int depth){ path.push(currentNode); if (depth >= 0) { //As long as we are depth > or equal zero, we are allowed to check for its predicate //Return if the node equals the goal. if (toSearchFor.test(currentNode)) return currentNode; for (Node currentChildNode : currentNode.adjacent()) { if (path.contains(currentChildNode)) continue; //If the current child is already in the stack path, continue. //Recursively search for the result node. Node result = searchForNode(currentChildNode, toSearchFor, depth - 1); if (result != null) return result; } } //Limit reached, remove it from the stack. path.pop(); //We found nothing, return nothing. return null; } |
GBFS – Greedy Best-First Search
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private Function<Node, Double> heuristic; public GBFS(Function<Node, Double> heuristic) { this.heuristic = heuristic; } public Node search(Node start, Predicate<Node> endPredicate) { //Check if the start node is the endPredicate if (endPredicate.test(start)) return start; //The queue containing all the nodes we have to search for StablePriorityQueue<Double, Node> nodeQueue = new StablePriorityQueue<>(); //Add the start node as the head. The priority does not matter since we remove it anyway. nodeQueue.add(new Pair<>(heuristic.apply(start), start)); //Adjacent, definition from the handbook.pdf contain all neighbors. //That means, that we would search in a node which we already searched for at another position. //Because of the insertion and lookup time O(1) in both situations, we chose the HashSt. HashSet<Node> checkedNodes = new HashSet<>(); //Insert the start node into the hashset, since we are using it checkedNodes.add(start); //Repeat till we have no element in the queue left. while (nodeQueue.size() > 0) { Pair<Double, Node> currentNode = nodeQueue.remove(); if (endPredicate.test(currentNode.s)) return currentNode.s; //Nothing found. Add all it's children else currentNode.s.adjacent().stream() //Get the stream .filter(node -> !checkedNodes.contains(node)) //Filter only the nodes we did not visit yet. .forEach(node -> { nodeQueue.add(new Pair<>(heuristic.apply(node), node)); //Add the node to the priority queue to search for the result. checkedNodes.add(node); //Add the node to the hashset, so that we do not search for that again. }); } //We cant reach that state, but just in case return null. return null; } |
MM – MinMax Search
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private BiPredicate<Integer, Node> searchLimitingPredicate; private int depth; /** * To limit the extent of the search, this implementation should honor a * limiting predicate. The predicate returns 'true' as long as we are below * the limit, and 'false', if we exceed the limit. * * @param searchLimitingPredicate */ public MinMaxSearch(BiPredicate<Integer, Node> slp) { this.searchLimitingPredicate = slp; depth = 0; } public Pair<Node, Double> search(Node start, Function<Node, Double> evalFunction) { Node winner = start; double value = Double.NEGATIVE_INFINITY; for (Node n : start.adjacent()) { double temp = min(n, evalFunction); if (temp > value) { value = temp; winner = n; } depth = 0; } return new Pair<Node, Double>(winner, value); } private double min(Node node, Function<Node, Double> evalFunction) { if (node.isLeaf() || !searchLimitingPredicate.test(depth+1, node)) { return evalFunction.apply(node); } depth++; double value = Double.POSITIVE_INFINITY; for (Node n : node.adjacent()) { value = Math.min(value, max(n, evalFunction)); } depth--; return value; } private double max(Node node, Function<Node, Double> evalFunction) { if (node.isLeaf() || !searchLimitingPredicate.test(depth+1, node)) { return evalFunction.apply(node); } depth++; double value = Double.NEGATIVE_INFINITY; for (Node n : node.adjacent()) { value = Math.max(value, min(n, evalFunction)); } depth--; return value; } |
A* – AStar
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private Function<Node, Double> heuristic; private Function<Node, Double> cost; public ASTAR(Function<Node, Double> heuristic, Function<Node, Double> cost) { this.heuristic = heuristic; this.cost = cost; } //A class to store heuristic and costs and also the possibility to compare each other. private class CostPair implements Comparable<CostPair> { private double heuristic; private double cost; private CostPair(double heuristic, double cost) { this.heuristic = heuristic; this.cost = cost; } @Override public int compareTo(CostPair other) { return Double.compare(heuristic + cost, other.heuristic + other.cost); } } public Node search(Node start, Predicate<Node> endPredicate) { // Check if the start node is the endPredicate if (endPredicate.test(start)) return start; // The queue containing all the nodes we have to search for StablePriorityQueue<CostPair, Node> nodeQueue = new StablePriorityQueue<>(); // Add the start node as the head. The priority does not matter since we // remove it anyway. nodeQueue.add(new Pair<>(new CostPair(heuristic.apply(start), cost.apply(start)), start)); // Adjacent, definition from the handbook.pdf contain all neighbors. // That means, that we would search in a node which we already searched for at another position. // Because of the insertion and lookup time O(1) in both situations, we chose the HashSt. HashSet<Node> checkedNodes = new HashSet<>(); // Repeat till we have no element in the queue left. while (nodeQueue.size() > 0) { Pair<CostPair, Node> currentNode = nodeQueue.poll(); if (endPredicate.test(currentNode.s)) return currentNode.s; // Nothing found. Add all it's children currentNode.s.adjacent().stream().filter(node -> !checkedNodes.contains(node)) .forEach(node -> { CostPair pair = new CostPair(heuristic.apply(node), currentNode.f.cost + cost.apply(node)); nodeQueue.add(new Pair<>(pair, node)); checkedNodes.add(currentNode.s); //Add the node to the hashset, so that we do not search for that again. }); } // We cant reach that state, but just in case return null. return null; } |
UCS – Uniform Cost-Search
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private Function<Node, Double> cost; public UCS(Function<Node, Double> cost) { this.cost = cost; } public Node search(Node start, Predicate<Node> endPredicate) { //The queue containing all the nodes we have to search for StablePriorityQueue<Double, Node> nodeQueue = new StablePriorityQueue<>(); //Add the start node as the head. The priority does not matter since we remove it anyway. nodeQueue.add(new Pair<>(cost.apply(start), start)); //Adjacent, definition from the handbook.pdf contain all neighbors. //That means, that we would search in a node which we already searched for at another position. //Because of the insertion and lookup time O(1) in both situations, we chose the HashSt. HashSet<Node> checkedNodes = new HashSet<>(); //Insert the start node into the hashset, since we are using it checkedNodes.add(start); //Repeat till we have no element in the queue left. while (nodeQueue.size() > 0) { Pair<Double, Node> currentNode = nodeQueue.poll(); if (endPredicate.test(currentNode.s)) return currentNode.s; //Nothing found. Add all it's children else currentNode.s.adjacent().stream() //Get the stream .filter(node -> !checkedNodes.contains(node)) //Filter only the nodes we did not visit yet. .forEach(node -> { nodeQueue.add(new Pair<>(cost.apply(node) + currentNode.f, node)); //Add the node to the priority queue to search for the result. checkedNodes.add(node); //Add the node to the hashset, so that we do not search for that again. }); } //We cant reach that state, but just in case return null. return null; } |
BFS – Breadth-First Search
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public Node search(Node start, Predicate<Node> endPredicate) { //Check if the start node is the endPredicate if(endPredicate.test(start)) return start; //The queue containing all the nodes we have to search for //We used ArrayDeque because it has the best performance of all queues. ArrayDeque<Node> nodeQueue = new ArrayDeque<>(start.adjacent()); //Adjacent, definition from the handbook.pdf contain all neighbors. //That means, that we would search in a node which we already searched for at another position. //Because of the insertion and lookup time O(1) in both situations, we chose the HashSet. HashSet<Node> checkedNodes = new HashSet<>(); //Repeat till we have no element in the queue left. while(nodeQueue.size() > 0) { Node currentNode = nodeQueue.removeFirst(); if(endPredicate.test(currentNode)) return currentNode; //The current node does not equal the predicate we //are searching for. Add all node's adjacent which we did not checked yet. currentNode.adjacent().stream().filter(node -> !checkedNodes.contains(node)).forEach(node -> { nodeQueue.addLast(node); //Add it to the queue checkedNodes.add(node); //Add it to the hasSet }); } //We cant reach that state, but just in case return null. return null; } |
