list - 逐渐增长的单元阵列类

Question

我编写了以下类来在 matlab 中实现“逐渐增长”的元胞数组:

classdef growinglist < handle 
    properties (GetAccess='private',SetAccess='private')
        inner_cells % inner pre-allocated cell array
    end
    properties (GetAccess='public',SetAccess='private')
        n_elements % current number of elements (index of last valid element in inner_cells)
    end
    methods
        %% constructor
        function self=growinglist(varargin)
            % you can pass the initial capacity of inner_cells to constructor
            if nargin == 1 
                self.inner_cells =cell(ceil(varargin{1}),1);
            else
                self.inner_cells =cell(4,1); % initial size is 4
            end
            self.n_elements = 0;
        end
        function add(self, element)
            % inner_cells is not enough, double it before adding
            if self.n_elements + 1 > size(self.inner_cells,1)
                n = floor(size(self.inner_cells,1) * 2) - size(self.inner_cells,1) + 1;
                self.inner_cells = [self.inner_cells; cell(n,1)];
            end
            self.n_elements = self.n_elements + 1;
            self.inner_cells{self.n_elements} = element;
        end
        function elements = get_elements(self)
            elements = self.inner_cells(1:self.n_elements,1);
        end
    end
end

但是，似乎并没有想象中那么快。

事实上，执行这些测试:

n = 30000;

%%%%%% concat everytime
tic
lst = {};
for i=1:n
    lst = [lst; 1:10];
end
disp('1 - concat everytime');
toc
%%%%%% exact pre-allocation
tic
lst = cell(n,1);
for i=1:n
    lst{i} = 1:10;
end
disp('2 - exact pre-allocation');
toc
%%%%%% "progressive" pre-allocation
tic
inner_cells = cell(4,1);
n_elements = 0;
for i=1:n
    if n_elements + 1 > size(inner_cells,1)
       n1 = floor(size(inner_cells,1) * 2) - size(inner_cells,1) + 1;
       inner_cells = [inner_cells; cell(n1,1)];
    end
    n_elements = n_elements+1;
    inner_cells{n_elements} = 1:10;
end
elements = inner_cells(1:n_elements,1);
disp('3 - "progressive" pre-allocation');
toc
%%%%%% using growing list class
tic
glst = growinglist();
for i=1:n
    glst.add(1:10);
end
elements = glst.get_elements();
disp('4 - using growing list class');
toc
%%%%%% using growing list class with exact allocation
tic
glst = growinglist(n);
for i=1:n
    glst.add(1:10);
end
elements = glst.get_elements();
disp('5 - use growing list class with exact allocation');
toc

我得到以下结果:

1 - concat everytime
Elapsed time is 4.954054 seconds.
2 - exact pre-allocation
Elapsed time is 0.006791 seconds.
3 - "progressive" pre-allocation
Elapsed time is 0.099431 seconds.
4 - using growing list class
Elapsed time is 11.618202 seconds.
5 - use growing list class with exact allocation
Elapsed time is 12.774726 seconds.

实际上，我预计测试 n.4 和 n.5 的运行时间会更接近测试 n.3。 但它们甚至比测试 n.1 慢(我预计这是最差的)。此外，奇怪的是，测试 n.5 比 n.4 慢。

也许每次设置或执行其他一些副本时都会复制inner_cells数组，但我不明白为什么，因为我从句柄类派生了我的类以支持可变性。

我对 matlab 还很陌生，所以可能我错过了一些重要的东西......
有什么见解吗？

提前致谢。

附注
我使用的是 MATLAB 2011a。

---

编辑:

根据建议 @Edric，我使用分析器找到了瓶颈，我发现了罪魁祸首 缓慢是在方法 Add() 中调用的 size(self.inner_cells,1) 函数(不知道为什么)。

以这种方式修改类(以减少 size() 调用):

classdef growinglist < handle 
    properties (GetAccess='private',SetAccess='private')
        inner_cells
        inner_cells_size
    end
    properties (GetAccess='public',SetAccess='private')
        n_elements % current number of elements (index of last valid element in inner_cells)
    end
    methods
        % constructor
        function self=growinglist(varargin)
            % you can pass the initial capacity of inner_cells to constructor
            if nargin == 1 
                self.inner_cells =cell(ceil(varargin{1}),1);
                self.inner_cells_size = ceil(varargin{1});
            else
                self.inner_cells =cell(4,1); % initial size is 4
                self.inner_cells_size = 4;
            end
            self.n_elements = 0;
        end
        function add(self, element)
            % inner_cells is not enough, double it before adding
            if self.n_elements + 1 > self.inner_cells_size
                n = floor(size(self.inner_cells,1) * 2) - size(self.inner_cells,1) + 1;
                self.inner_cells = [self.inner_cells; cell(n,1)];
                self.inner_cells_size = self.inner_cells_size + n;
            end
            self.n_elements = self.n_elements + 1;
            self.inner_cells{self.n_elements} = element;
        end
        function elements = get_elements(self)
            elements = self.inner_cells(1:self.n_elements,1);
        end
    end
end

现在测试结果:

1 - concat everytime
Elapsed time is 6.825776 seconds.
2 - exact pre-allocation
Elapsed time is 0.011783 seconds.
3 - "progressive" pre-allocation
Elapsed time is 0.088668 seconds.
4 - using growing list class
Elapsed time is 0.841975 seconds.
5 - use growing list class with exact allocation
Elapsed time is 0.818212 seconds.

这更有意义。

Answer 1

不幸的是，与内置功能相比，MATLAB 对象系统通常很慢 - 特别是当您运行数千个方法调用时，每个方法调用只执行少量的计算，就像在本例中一样。

可能有帮助的一件事是使用函数调用样式进行方法调用(不确定是否有更好的术语)。无论如何，它看起来像这样:

add(glst, 1:10);

而不是

glst.add(1:10);

这使得 MATLAB 能够立即意识到您指的是方法调用而不是字段引用。