逐步增长的单元阵列类

Question

我编写了以下类，以便在matlab中实现“逐步增长”的单元格数组：

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

然而，它似乎并不像预期的那样快。

实际上，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所用的时间更接近测试n.3。但他们甚至比测试n.1慢(我预计这将是最坏的)。此外，奇怪的是，测试n.5比n.4慢。

也许每次设置inner_cells数组时都会复制该数组，或者修改其他一些副本，但我不明白为什么，因为我从handle类派生了类以支持可变性。

我刚加入matlab所以我可能遗漏了一些重要的东西..。

有洞察力吗？

提前谢谢。

附注：

我正在使用MATLAB 2011 a。

编辑:

正如@Edric所建议的那样，我使用分析器查找瓶颈，并发现慢度的罪魁祸首是在方法Add() (--不知道为什么是)中调用的函数。

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

试验现在产生：

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.

这更有道理。

Answer 1

不幸的是，与内置功能相比，MATLAB对象系统通常要慢一些--特别是当您运行数千个方法调用时，每个调用只执行微不足道的计算量，就像在本例中一样。

一件可能有用的事情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，它看起来是这样的：

add(glst, 1:10);

而不是

glst.add(1:10);

这使得MATLAB可以立即意识到，您指的是方法调用，而不是字段引用。