bin2mat運行緩慢需要更快的解決方案

Question

我使用bin2mat函數從matlab文件交換，由於某些原因它運行速度非常慢。是否有可能使其運行得更快或有其他選擇？我在嘗試：zC = bin2mat（s.X，s.Y，s.Z，xC，yC）;我不確定它在哪裏陷入困境。我需要在點雲數據上執行此操作來計算音量等。

下面是代碼：

function ZG = bin2mat(x,y,z,XI,YI,varargin) 
% BIN2MAT - create a matrix from scattered data without interpolation 
% 
% ZG = BIN2MAT(X,Y,Z,XI,YI) - creates a grid from the data 
% in the (usually) nonuniformily-spaced vectors (x,y,z) 
% using grid-cell averaging (no interpolation). The grid 
% dimensions are specified by the uniformily spaced vectors 
% XI and YI (as produced by meshgrid). 
% 
% ZG = BIN2MAT(...,@FUN) - evaluates the function FUN for each 
% cell in the specified grid (rather than using the default 
% function, mean). If the function FUN returns non-scalar output, 
% the output ZG will be a cell array. 
% 
% ZG = BIN2MAT(...,@FUN,ARG1,ARG2,...) provides aditional 
% arguments which are passed to the function FUN. 
% 
% EXAMPLE 
%  
% %generate some scattered data 
% [x,y,z]=peaks(150); 
% ind=(rand(size(x))>0.9); 
% xs=x(ind); ys=y(ind); zs=z(ind); 
% 
% %create a grid, use lower resolution if 
% %no gaps are desired 
% xi=min(xs):0.25:max(xs); 
% yi=min(ys):0.25:max(ys); 
% [XI,YI]=meshgrid(xi,yi); 
% 
% %calculate the mean and standard deviation 
% %for each grid-cell using bin2mat 
% Zm=bin2mat(xs,ys,zs,XI,YI); %mean 
% Zs=bin2mat(xs,ys,zs,XI,YI,@std); %std 
% 
% %plot the results 
% figure 
% subplot(1,3,1); 
% scatter(xs,ys,10,zs,'filled') 
% axis image 
% title('Scatter Data')  
% 
% subplot(1,3,2); 
% pcolor(XI,YI,Zm) 
% shading flat 
% axis image 
% title('Grid-cell Average') 
% 
% subplot(1,3,3); 
% pcolor(XI,YI,Zs) 
% shading flat 
% axis image 
% title('Grid-cell Std. Dev.') 
% 
% SEE also RESHAPE ACCUMARRAY FEVAL 

% A. Stevens 3/10/2009 
% astevens@usgs.gov 

%check inputs 
error(nargchk(5,inf,nargin,'struct')); 

%make sure the vectors are column vectors 
x = x(:); 
y = y(:); 
z = z(:); 

if all(any(diff(cellfun(@length,{x,y,z})))); 
    error('Inputs x, y, and z must be the same size'); 
end 

%process optional input 
fun=@mean; 
test=1; 
if ~isempty(varargin) 
    fun=varargin{1}; 
    if ~isa(fun,'function_handle'); 
     fun=str2func(fun); 
    end 

    %test the function for non-scalar output 
    test = feval(fun,rand(5,1),varargin{2:end}); 

end 

%grid nodes 
xi=XI(1,:); 
yi=YI(:,1); 
[m,n]=size(XI); 

%limit values to those within the specified grid 
xmin=min(xi); 
xmax=max(xi); 
ymin=min(yi); 
ymax=max(yi); 

gind =(x>=xmin & x<=xmax & ... 
    y>=ymin & y<=ymax); 

%find the indices for each x and y in the grid 
[junk,xind] = histc(x(gind),xi); 
[junk,yind] = histc(y(gind),yi); 

%break the data into a cell for each grid node 
blc_ind=accumarray([yind xind],z(gind),[m n],@(x){x},{NaN}); 

%evaluate the data in each grid using FUN 
if numel(test)>1 
    ZG=cellfun(@(x)(feval(fun,x,varargin{2:end})),blc_ind,'uni',0); 
else 
    ZG=cellfun(@(x)(feval(fun,x,varargin{2:end})),blc_ind); 
end 

正是在這兩個步驟爲一個運行它採取慢： ZG=cellfun(@(x)(feval(fun,x,varargin{2:end})),blc_ind);了33秒 blc_ind=accumarray([yind xind],z(gind),[m n],@(x){x},{NaN});花了10秒

Answer 1

您可以更改blc_ind = ...到

ZG=accumarray([yind xind],z(gind),[m n],@mean,NaN); 

並在此刪除其他代碼，因此不需要if numel(test)>1....