我正在尝试了解catamorphisms,我已经阅读了维基百科文章以及F#博客上F#主题系列中的第一篇文章.
我理解这是折叠的概括(即,将许多值的结构映射到一个值,包括值列表到另一个列表).我认为折叠列表和折叠树是一个典型的例子.
可以使用LINQ的Aggregate
运算符或其他一些更高阶的方法在C#中显示它吗?
LINQ的Aggregate()仅适用于IEnumerables.Catatorphisms通常指的是任意数据类型的折叠模式.所以Aggregate()是IEnumerables FoldTree(下面)对Trees(下图)的内容; 两者都是各自数据类型的catamorphisms.
我将系列的第4部分中的一些代码翻译成了C#.代码如下.请注意,等效的F#使用了三个小于字符(对于泛型类型参数注释),而这个C#代码使用了超过60个.这就是为什么没有人在C#中编写这样的代码的证据 - 有太多的类型注释.我提供代码,以防它知道C#而不是F#的人玩这个.但是C#中的代码非常密集,很难理解.
给定二叉树的以下定义:
using System; using System.Collections.Generic; using System.Windows; using System.Windows.Controls; using System.Windows.Input; using System.Windows.Media; using System.Windows.Shapes; class Tree// use null for Leaf { public T Data { get; private set; } public Tree Left { get; private set; } public Tree Right { get; private set; } public Tree(T data, Tree left, Tree rright) { this.Data = data; this.Left = left; this.Right = right; } public static Tree Node (T data, Tree left, Tree right) { return new Tree (data, left, right); } }
人们可以折叠树木,例如测量两棵树是否有不同的节点:
class Tree { public static TreeTree7 = Node(4, Node(2, Node(1, null, null), Node(3, null, null)), Node(6, Node(5, null, null), Node(7, null, null))); public static R XFoldTree(Func, R> nodeF, Func , R> leafV, Tree tree) { return Loop(nodeF, leafV, tree, x => x); } public static R Loop(Func, R> nodeF, Func , R> leafV, Tree t, Func cont) { if (t == null) return cont(leafV(t)); else return Loop(nodeF, leafV, t.Left, lacc => Loop(nodeF, leafV, t.Right, racc => cont(nodeF(t.Data, lacc, racc, t)))); } public static R FoldTree(Func nodeF, R leafV, Tree tree) { return XFoldTree((x, l, r, _) => nodeF(x, l, r), _ => leafV, tree); } public static Func , Tree> XNode(A x, Tree l, Tree r) { return (Tree t) => x.Equals(t.Data) && l == t.Left && r == t.Right ? t : Node(x, l, r); } // DiffTree: Tree<'a> * Tree<'a> -> Tree<'a * bool> // return second tree with extra bool // the bool signifies whether the Node "ReferenceEquals" the first tree public static Tree > DiffTree(Tree tree, Tree tree2) { return XFoldTree((A x, Func , Tree >> l, Func , Tree >> r, Tree t) => (Tree t2) => Node(new KeyValuePair(t2.Data, object.ReferenceEquals(t, t2)), l(t2.Left), r(t2.Right)), x => y => null, tree)(tree2); } }
在第二个示例中,另一个树的重建方式不同:
class Example { // original version recreates entire tree, yuck public static TreeChange5to0(Tree tree) { return Tree.FoldTree((int x, Tree l, Tree r) => Tree.Node(x == 5 ? 0 : x, l, r), null, tree); } // here it is with XFold - same as original, only with Xs public static Tree XChange5to0(Tree tree) { return Tree.XFoldTree((int x, Tree l, Tree r, Tree orig) => Tree.XNode(x == 5 ? 0 : x, l, r)(orig), _ => null, tree); } }
在第三个例子中,折叠树用于绘图:
class MyWPFWindow : Window { void Draw(Canvas canvas, Tree> tree) { // assumes canvas is normalized to 1.0 x 1.0 Tree.FoldTree((KeyValuePair kvp, Func l, Func r) => trans => { // current node in top half, centered left-to-right var tb = new TextBox(); tb.Width = 100.0; tb.Height = 100.0; tb.FontSize = 70.0; // the tree is a "diff tree" where the bool represents // "ReferenceEquals" differences, so color diffs Red tb.Foreground = (kvp.Value ? Brushes.Black : Brushes.Red); tb.HorizontalContentAlignment = HorizontalAlignment.Center; tb.VerticalContentAlignment = VerticalAlignment.Center; tb.RenderTransform = AddT(trans, TranslateT(0.25, 0.0, ScaleT(0.005, 0.005, new TransformGroup()))); tb.Text = kvp.Key.ToString(); canvas.Children.Add(tb); // left child in bottom-left quadrant l(AddT(trans, TranslateT(0.0, 0.5, ScaleT(0.5, 0.5, new TransformGroup())))); // right child in bottom-right quadrant r(AddT(trans, TranslateT(0.5, 0.5, ScaleT(0.5, 0.5, new TransformGroup())))); return null; }, _ => null, tree)(new TransformGroup()); } public MyWPFWindow(Tree > tree) { var canvas = new Canvas(); canvas.Width=1.0; canvas.Height=1.0; canvas.Background = Brushes.Blue; canvas.LayoutTransform=new ScaleTransform(200.0, 200.0); Draw(canvas, tree); this.Content = canvas; this.Title = "MyWPFWindow"; this.SizeToContent = SizeToContent.WidthAndHeight; } TransformGroup AddT(Transform t, TransformGroup tg) { tg.Children.Add(t); return tg; } TransformGroup ScaleT(double x, double y, TransformGroup tg) { tg.Children.Add(new ScaleTransform(x,y)); return tg; } TransformGroup TranslateT(double x, double y, TransformGroup tg) { tg.Children.Add(new TranslateTransform(x,y)); return tg; } [STAThread] static void Main(string[] args) { var app = new Application(); //app.Run(new MyWPFWindow(Tree.DiffTree(Tree.Tree7,Example.Change5to0(Tree.Tree7)))); app.Run(new MyWPFWindow(Tree.DiffTree(Tree.Tree7, Example.XChange5to0(Tree.Tree7)))); } }
我一直在做更多阅读,包括关于使用catamorphisms("香蕉")进行函数式编程的Micorosft Research论文,似乎catamorphism只是指任何采用列表并通常将其分解为单个值(IEnumerable => B
)的函数,像Max(),Min(),在一般情况下,Aggregate(),都是列表的catamorphisms.
我之前的印象是它提到了一种创建可以概括不同折叠的函数的方法,因此它可以折叠树和列表.实际上可能还有这样的东西,某种类型的仿函数或箭头,但现在这超出了我的理解水平.
Brian在第一段中的答案是正确的。但是他的代码示例并未真正反映出如何以C#样式解决类似问题。考虑一个简单的类node
:
class Node { public Node Left; public Node Right; public int value; public Node(int v = 0, Node left = null, Node right = null) { value = v; Left = left; Right = right; } }
这样我们可以在main中创建一棵树:
var Tree = new Node(4, new Node(2, new Node(1), new Node(3) ), new Node(6, new Node(5), new Node(7) ) );
我们在Node
的命名空间中定义了通用的fold函数:
public static R fold( Func combine, R leaf_value, Node tree) { if (tree == null) return leaf_value; return combine( tree.value, fold(combine, leaf_value, tree.Left), fold(combine, leaf_value, tree.Right) ); }
对于变形,我们应指定数据状态,节点可以为空或有子级。通用参数决定了我们在这两种情况下的操作。注意迭代策略(在这种情况下为递归)隐藏在fold函数中。
现在不用写:
public static int Sum_Tree(Node tree){ if (tree == null) return 0; var accumulated = tree.value; accumulated += Sum_Tree(tree.Left); accumulated += Sum_Tree(tree.Right); return accumulated; }
我们可以写
public static int sum_tree_fold(Node tree) { return Node.fold( (x, l, r) => x + l + r, 0, tree ); }
优雅,简单,经过类型检查,可维护等。易于使用Console.WriteLine(Node.Sum_Tree(Tree));
。
添加新功能很容易:
public static ListIn_Order_fold(Node tree) { return Node.fold( (x, l, r) => { var tree_list = new List (); tree_list.Add(x); tree_list.InsertRange(0, l); tree_list.AddRange(r); return tree_list; }, new List (), tree ); } public static int Height_fold(Node tree) { return Node.fold( (x, l, r) => 1 + Math.Max(l, r), 0, tree ); }
F#在“简洁”类别中获胜,In_Order_fold
但是当该语言提供了用于构造和使用列表的专用运算符时,这是可以预期的。
C#和F#之间的巨大差异似乎是由于F#使用闭包来充当隐式数据结构来触发尾部调用优化。Brian的答案中的示例还考虑了F#中的优化,以躲避重构树。我不确定C#是否支持尾部调用优化,也许In_Order_fold
可以写得更好,但是在讨论处理这些Catamorphism时C#的表现力如何时,这些要点都不重要。
在语言之间翻译代码时,您需要了解该技术的核心思想,然后根据语言的原语来实现该思想。
也许现在您可以说服您的C#同事更加认真地对待折叠。