当我使用nlfilter函数时如何输出结构数组？ [英] How to output a struct array when I use the nlfilter function?

问题描述

我有以下函数来计算统计参数。我想将这个函数传递给 nlfilter 来完成整个图像的计算。但是 nlfilter 的输出必须是标量。

如何将其转换为适合使用的函数句柄使用 nlfilter ，所以我可以保存函数的输出 getStatistics2 ？

getStatistics2 函数的输出是一个 struct 数组。

  function [out] = getStatistics2（D）
 D = double（D）; 
％out.MAX = max（D）;％最大
％out.MIN = min（D）;％最小
 out.MEA =均值（D）;％均值
 out.MAD = mad（D）;％平均绝对偏差y =平均值（abs（X-mean（x）））
 out.MED = median（D）;％median 
 out.RAN = D（D） -  min（D）;％范围
 out.RMS = rms（D）;％均方根
 out.STD = std（D）;％标准偏差
 out.VAR = var（D）;％variance 
  

解决方案

这是个有趣的问题。有趣的是你的方法几乎是完美的。它失败的唯一原因是因为 struct 不能使用数字标量输入（即 struct（3））来构造。我提到这个的原因是因为在执行 nlfilter （具体在 mkconstarray.m ），它会调用下面的代码：

$ $ $ $ $ $ $ $> repmat（feval（class，value），size）;

其中：

class 是'struct'。

• value 是 0 。


• size 是输入图像的 size（），例如 [100,100] 。

...因为 feval（'struct'，0），这相当于 struct（0） - 这个我们已经知道是无效的了。

那么我们该怎么做？创建一个可以用这种方式构造 的自定义类！

下面是一个这样的类的例子：

  classdef MyStatsClass％Value类
 
（GetAccess = public，SetAccess = private）
 MAX @ double scalar = NaN; ％最大
 MIN @ double scalar = NaN; ％最小
 MEA @ double scalar = NaN; ％均值
 MAD @ double scalar = NaN; ％平均绝对偏差y =平均值（abs（X-mean（x）））
 MED @ double scalar = NaN; ％中位数
 RMS @ double scalar = NaN; ％均方根
 STD @ double scalar = NaN; ％标准差
 VAR @ double scalar = NaN; ％差异
 RAN @ double scalar = NaN; ％范围
结束％属性
 
方法（Access = public）
 %%构造函数：
函数obj = MyStatsClass（vec）
 %%特例：
 if（nargin == 0）|| （numel（vec）== 1）&& （vec == 0）
％nlfilter分配过程中发生
返回
结束
 %%常规情况：
 obj.MAX = max（vec（:)） ; 
 obj.MIN = min（vec（:)）; 
 obj.MEA = mean（vec（:)）; 
 obj.MAD = mad（vec（:)）; 
 obj.MED = median（vec（:)）; 
 obj.RMS = rms（vec（:)）; 
 obj.STD = std（vec（:)）; 
 obj.VAR = var（vec（:)）; 
 obj.RAN = obj.MAX  -  obj.MIN; 
结束％默认构造函数
结束％公共方法
结束％classdef 
  

<

  function imF = q35693068（outputAsStruct）
 if nargin == 0 || 〜islogical（outputAsStruct）|| 〜isscalar（outputAsStruct）
 outputAsStruct = false; 
 end 
 
 rng（35693068）; ％设置随机种子，重复性
 WINDOW_SZ = 3; 
 im = randn（100）; 
 imF = nlfilter（im，[WINDOW_SZ WINDOW_SZ]，@MyStatsClass）; 
 
如果输出是严格需要的结构：
如果outputAsStruct 
警告关闭MATLAB：structOnObject 
 imF = arrayfun（@ struct，imF）; 
在MATLAB的警告：structOnObject 
结束
  

请注意，我添加了一个可选输入（ outputAsStruct ）可以强制输出为 struct 数组（而不是我们类型的数组自定义类，它在功能上与只读 struct ）相同。

注意，默认情况下 nlfilter 用零填充数组，这意味着（1,1）输出将在一个看起来像这样的数组上运行（假设 WINDOW_SZ = 3 ）：

  [0 0 0 
 0 1.8096 0.5189 
 0 -0.3434 0.6586] 
  

而不是 im（1：WINDOW_SZ，1：WINDOW_SZ）即：

  [1.8096 0.5189 0.2811 
 -0.3434 0.6586 0.8919 
 -0.1525 0.7549 0.4497] 
  

预期结果for im（1：WINDOW_SZ，1：WINDOW_SZ）将在outp ut数组（在 WINDOW_SZ = 3 的情况下，在索引（2,2））。

I have the following function which calculates statistic parameters. I would like to pass this function to nlfilter to do the calculation for a whole image. But the output of nlfilter must be a scalar.

How can I convert this to a function handle suitable for use with nlfilter so I can save the output of the function getStatistics2?

The getStatistics2 function's output is an struct array.

function [out] = getStatistics2(D)
D = double(D);   
% out.MAX = max(D);%maximum
% out.MIN = min(D);%minimum
out.MEA = mean(D);%mean
out.MAD = mad(D);% mean absolute deviation y=mean(abs(X-mean(x)))
out.MED = median(D);%median
out.RAN = max(D) - min(D);%range
out.RMS = rms(D);%root mean square
out.STD = std(D);%stardard deviation
out.VAR= var(D);%variance

解决方案

This is an interesting question. What's interesting is that your approach is almost perfect. The only reason it fails is because struct cannot be constructed using a numeric scalar input (i.e. struct(3)). The reason I mention this is because somewhere during the execution of nlfilter (specifically in mkconstarray.m), it calls the the following code:

repmat(feval(class, value), size);

Where:

• class is 'struct'.
• value is 0.
• size is the size() of the input image, e.g. [100,100].

... and this fails because feval('struct', 0), which is equivalent to struct(0) - and this we already know to be invalid.

So what do we do? Create a custom class that can be constructed this way!

Here's an example of one such class:

classdef MyStatsClass % Value class

  properties (GetAccess = public, SetAccess = private)
    MAX@double scalar = NaN;  % Maximum
    MIN@double scalar = NaN;  % Minimum
    MEA@double scalar = NaN;  % Mean
    MAD@double scalar = NaN;  % Mean absolute deviation y = mean(abs(X-mean(x)))
    MED@double scalar = NaN;  % Median
    RMS@double scalar = NaN;  % Root mean square
    STD@double scalar = NaN;  % Stardard deviation
    VAR@double scalar = NaN;  % Variance
    RAN@double scalar = NaN;  % Range    
  end % properties

  methods (Access = public)
    %% Constructor:
    function obj = MyStatsClass(vec)
      %% Special case:
      if (nargin == 0) || (numel(vec) == 1) && (vec == 0)
        % This happens during nlfilter allocation
        return
      end      
      %% Regular case:
      obj.MAX = max(vec(:));       
      obj.MIN = min(vec(:));
      obj.MEA = mean(vec(:));
      obj.MAD = mad(vec(:));
      obj.MED = median(vec(:));
      obj.RMS = rms(vec(:));
      obj.STD = std(vec(:));
      obj.VAR = var(vec(:));
      obj.RAN = obj.MAX - obj.MIN;
    end % default constructor
  end % public methods
end % classdef

And here's how you can use it:

function imF = q35693068(outputAsStruct)
if nargin == 0 || ~islogical(outputAsStruct) || ~isscalar(outputAsStruct)
  outputAsStruct = false;
end

rng(35693068); % Set the random seed, for repeatability
WINDOW_SZ = 3;
im = randn(100);
imF = nlfilter(im, [WINDOW_SZ WINDOW_SZ], @MyStatsClass);

% If output is strictly needed as a struct:
if outputAsStruct
  warning off MATLAB:structOnObject
  imF = arrayfun(@struct,imF);
  warning on MATLAB:structOnObject
end

Notice that I have added an optional input (outputAsStruct) that can force the output to be a struct array (and not an array of the type of our custom class, which is functionally identical to a read-only struct).

Notice also that by default nlfilter pads your array with zeros, which means that the (1,1) output will operate on an array that looks like this (assuming WINDOW_SZ=3):

[0    0      0    
 0  1.8096 0.5189 
 0 -0.3434 0.6586]

and not on im(1:WINDOW_SZ,1:WINDOW_SZ) which is:

[ 1.8096 0.5189 0.2811
 -0.3434 0.6586 0.8919
 -0.1525 0.7549 0.4497]

the "expected result" for im(1:WINDOW_SZ,1:WINDOW_SZ) will be found further "inside" the output array (in the case of WINDOW_SZ=3 at index (2,2)).

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