访问 N(未知)维矩阵中所有点的算法

发布于 2024-09-15 16:13:36 字数 720 浏览 3 评论 0原文

我有一个多维矩阵,可以具有大于一的任意维数。寻找一种可以访问矩阵中每个点的有效算法。

有关代码的一些信息: 该矩阵具有类似的值访问器(尽管这些并不真正相关)。

object value = matrixInstance.GetValue(int[] point);   
matrixInstance.SetValue(object value, int[] point);  

注意:参数 point 是索引数组,必须与维度数匹配,否则会引发异常。

有关矩阵结构的信息可以通过以下方式获得:

int numDims = matrixInstance.Rank; //# dimensions
int sizeDim = matrix.getRankSize(int index); // length of specified dimension

我想使用相对有效的算法迭代矩阵的所有可能点。

例如,在 2x3 2D 矩阵中,将访问以下六个点:
[0,0] [0,1] [0,2] [1,0] [1,1] [1,2]

该算法必须工作到 N 维:2、3、4 等。为了提高效率,我最终将使用 C# 迭代器 返回点。

I have a multidimensional matrix that can have any number of dimensions greater than one. Looking for an efficient algorithm that can visit every point in the matrix.

Some info about the code:
The matrix has value accessors like (although these aren't really relevant).

object value = matrixInstance.GetValue(int[] point);   
matrixInstance.SetValue(object value, int[] point);  

Note: Argument point is array of indexes and must match # of dimensions or an exception is thrown.

Information about the matrix structure can be garnered by:

int numDims = matrixInstance.Rank; //# dimensions
int sizeDim = matrix.getRankSize(int index); // length of specified dimension

I want to iterate over all possible points of the matrix using a relatively efficient algorithm.

For example, in a 2x3 2D matrix the following six points would be visited:
[0,0]
[0,1]
[0,2]
[1,0]
[1,1]
[1,2]

The algorithm must work up to N dimensions: 2,3,4,etc. For efficiency I'll end up using a C# iterator to return the points.

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评论(4

青春如此纠结 2024-09-22 16:13:36

您可以将矩阵视为一棵在叶子上具有所有值的树:

        Illustration

是矩阵

[0,0] = 'A'
[0,1] = 'B'
[1,0] = 'C'
[1,1] = 'D'

只需应用任何众所周知的树遍历解决方案即可。


这是一个递归解决方案(未经测试):

IEnumerable<Point> GetPoints(Matrix matrix, int[] indexes)
{
    if (indexes.Length == matrix.Rank)
    {
        yield return matrix.GetValue(indexes);
    }
    else
    {
        for (int i = 0; i < matrix.GetRankSize(indexes.Length); i++)
        {
            foreach (var point in
                GetPoints(matrix, indexes.Concat(new int[] { i }).ToArray())
            {
                yield return point;
            }
        }
    }
}

将其转换为使用显式堆栈的迭代版本应该相当简单。

You can view your matrix an a tree that has all of its values at the leaves:

           Illustration

is the matrix

[0,0] = 'A'
[0,1] = 'B'
[1,0] = 'C'
[1,1] = 'D'

Just apply any well-known tree traversal solution.


Here is a recursive solution (untested):

IEnumerable<Point> GetPoints(Matrix matrix, int[] indexes)
{
    if (indexes.Length == matrix.Rank)
    {
        yield return matrix.GetValue(indexes);
    }
    else
    {
        for (int i = 0; i < matrix.GetRankSize(indexes.Length); i++)
        {
            foreach (var point in
                GetPoints(matrix, indexes.Concat(new int[] { i }).ToArray())
            {
                yield return point;
            }
        }
    }
}

It should be fairly trivial to convert this to an iterative version that uses an explicit stack.

鯉魚旗 2024-09-22 16:13:36

如果可以在运行时生成每个维度的索引值集合,则可以使用 Eric Lippert 的 LINQ 代码段,用于生成索引值的所有组合。

Eric 生成所有组合集合的方法:

static IEnumerable<IEnumerable<T>> CartesianProduct<T>(this IEnumerable<IEnumerable<T>> sequences) 
{ 
  IEnumerable<IEnumerable<T>> emptyProduct = new[] { Enumerable.Empty<T>() }; 
  return sequences.Aggregate( 
    emptyProduct, 
    (accumulator, sequence) =>  
      from accseq in accumulator  
      from item in sequence  
      select accseq.Concat(new[] {item}));                
}

因此,对于您的 2x3 示例,

int [ , ] dimensions= { { 0, 1}, { 0, 1, 2 } } ;
var allMatrixCells = CartesianProduct<int>(dimensions);

foreach(var cellLocation in allMatrixCells )
{
 ...
}

If you can generate a collection of index values for each dimension at run time, then you can use Eric Lippert's LINQ snippet to generate all combinations of the index values.

Eric's method to produce a collection of all combinations:

static IEnumerable<IEnumerable<T>> CartesianProduct<T>(this IEnumerable<IEnumerable<T>> sequences) 
{ 
  IEnumerable<IEnumerable<T>> emptyProduct = new[] { Enumerable.Empty<T>() }; 
  return sequences.Aggregate( 
    emptyProduct, 
    (accumulator, sequence) =>  
      from accseq in accumulator  
      from item in sequence  
      select accseq.Concat(new[] {item}));                
}

So, for your 2x3 example,

int [ , ] dimensions= { { 0, 1}, { 0, 1, 2 } } ;
var allMatrixCells = CartesianProduct<int>(dimensions);

foreach(var cellLocation in allMatrixCells )
{
 ...
}
月野兔 2024-09-22 16:13:36

简单地递归迭代每个维度。例如,第一次调用迭代第一个维度的每个值,调用自身迭代第二个维度的每个值,依此类推,无论您有多少个维度。然后,基本情况(当没有更多维度时)是返回相关单元格中的值,而不是再次递归。

Simply recursively iterate over each dimension. Eg, the first invocation iterates over every value for the first dimension, calling itself to iterate over every value for the second dimension, and so forth for however many dimensions you have. Then, the base case (when there are no more dimensions) is to return the value in the relevant cell, rather than recursing again.

灼痛 2024-09-22 16:13:36

您可以使用混合基数表示,请参见 http://en.wikipedia.org/wiki/Mixed_radix< /a>

例如,如果有 4 个维度,长度分别为 4,3,2,7,则对应于索引 a,b,c,d,我们有数字 a+4*(b+3*(c+2* d))。从中恢复索引
数字 n 就像获取十进制数字一样,只是基数不同,即
a = n%4; n/=4; b = n%3; n /= 3; c = n%2; n/=2; d = n。

因此,您将有一个 for 循环(在本例中为 n=0..4*3*2*7-1),其中索引可以
如上所述从 n 中恢复。

然而,也许所有这些划分和模数意味着这不是那么有效。

You could use a mixed radix representation, see eg http://en.wikipedia.org/wiki/Mixed_radix

For example if you had 4 dimensions with lengths 4,3,2,7 say then corresponding to the indices a,b,c,d we have the number a+4*(b+3*(c+2*d)). To recover the indices from
a number n is just like getting the decimal digits, except the base varies, ie
a = n%4; n /=4; b = n%3; n /= 3; c = n %2; n/=2; d = n.

So you would have one for loop (in this case for n=0..4*3*2*7-1) in which the indices could
be recovered from n as above.

However perhaps all those divisions and moduli would mean this isn't so efficient.

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