在matlab中，每次迭代后矩阵计算都会变慢

我有一个1024*1024*51的矩阵。我将进行计算以更改for循环中矩阵的某些值（更改每次迭代的矩阵值）。我发现计算速度越来越慢，最后我的电脑出了问题。但是矩阵的大小没有改变。谁能解释一下这个问题

function ActiveContours3D(method,grad,im,mu,nu,lambda1,lambda2,TimeSteps)
epsilon = 10e-10;
tic
fid=fopen('Chr18_z_25of25tiles-C=0_c0_n000.raw','rb','ieee-le');   
Xdim = 1024;
Ydim = 1024;
Zdim = 51;
A = fread(fid,[Xdim Ydim*Zdim],'int16');
A = double(A);
size_of_A = size(A)
for(i=1:Zdim)
    u0_color(:,:,i) = A(1 : Xdim , (i-1)*Ydim+1 : i*Ydim);
end
fclose(fid)

time = toc

[M,N,P,color] = size(u0_color);
size(u0_color );
u0_color = double(u0_color);    % Convert u0_color values to double;
u0 = u0_color(:,:,:,1);           % Define the Grayscale volumetric image.
u0_color = uint8(u0_color);     % Necessary for color visualization
x = 1:M;
y = 1:N;
z = 1:P;
dx = 1
dy = 1
dz = 1
dim_approx = 2*M*N*P / sqrt(M*N*P);
if(method == 'Explicit')
    dt = 0.9 / ((2*mu/(dx^2)) + (2*mu/(dy^2)) + (2*mu/(dz^2)))    % 90% CFL
elseif(method == 'Implicit')
    dt = (10e7) * 0.9 / ((2*mu/(dx^2)) + (2*mu/(dy^2)) + (2*mu/(dz^2)))
end
[X,Y,Z] = meshgrid(x,y,z);
x0 = (M+1)/2;
y0 = (N+1)/2;
z0 = (P+1)/2;
r0 = min(min(M,N),P)/3;
phi = sqrt((X-x0).^2 + (Y-y0).^2 + (Z-z0).^2) - r0; 
phi_visualize = phi;            % Use this for visualization in 3D
phi = permute(phi,[2,1,3]);     % Use this for computations in 3D
write_to_binary_file(phi_visualize,0);       % record initial conditions

tic

for(n=1:TimeSteps)
n

c1 = C1_3d(u0,phi);
c2 = C2_3d(u0,phi);

% x
phi_xp = [phi(2:M,:,:); phi(M,:,:)];      % vertical concatenation
phi_xm = [phi(1,:,:);   phi(1:M-1,:,:)];        % (since x values are rows)
                        % cat(1,A,B) is the same as [A;B]
Dx_m = (phi - phi_xm)/dx;           % first derivatives
Dx_p = (phi_xp - phi)/dx;

Dxx = (Dx_p - Dx_m)/dx;     % second derivative

% y
phi_yp = [phi(:,2:N,:) phi(:,N,:)];       % horizontal concatenation
phi_ym = [phi(:,1,:)   phi(:,1:N-1,:)];         % (since y values are columns)
                        % cat(2,A,B) is the same as [A,B]
Dy_m = (phi - phi_ym)/dy;
Dy_p = (phi_yp - phi)/dy;

Dyy = (Dy_p - Dy_m)/dy;

% z
phi_zp = cat(3,phi(:,:,2:P),phi(:,:,P));
phi_zm = cat(3,phi(:,:,1)  ,phi(:,:,1:P-1));

Dz_m = (phi - phi_zm)/dz;
Dz_p = (phi_zp - phi)/dz;

Dzz = (Dz_p - Dz_m)/dz;

% x,y,z
Dx_0 = (phi_xp - phi_xm) / (2*dx);
Dy_0 = (phi_yp - phi_ym) / (2*dy);
Dz_0 = (phi_zp - phi_zm) / (2*dz);

phi_xp_yp = [phi_xp(:,2:N,:) phi_xp(:,N,:)];
phi_xp_ym = [phi_xp(:,1,:)   phi_xp(:,1:N-1,:)];
phi_xm_yp = [phi_xm(:,2:N,:) phi_xm(:,N,:)];
phi_xm_ym = [phi_xm(:,1,:)   phi_xm(:,1:N-1,:)];

phi_xp_zp = cat(3,phi_xp(:,:,2:P),phi_xp(:,:,P));
phi_xp_zm = cat(3,phi_xp(:,:,1)  ,phi_xp(:,:,1:P-1));
phi_xm_zp = cat(3,phi_xm(:,:,2:P),phi_xm(:,:,P));
phi_xm_zm = cat(3,phi_xm(:,:,1)  ,phi_xm(:,:,1:P-1));

phi_yp_zp = cat(3,phi_yp(:,:,2:P),phi_yp(:,:,P));
phi_yp_zm = cat(3,phi_yp(:,:,1)  ,phi_yp(:,:,1:P-1));
phi_ym_zp = cat(3,phi_ym(:,:,2:P),phi_ym(:,:,P));
phi_ym_zm = cat(3,phi_ym(:,:,1)  ,phi_ym(:,:,1:P-1));    


if(grad == 'Dirac')
    Grad = DiracDelta(phi);                  % Dirac delta    
    %Grad = 1;
elseif(grad == 'Grad ')
    Grad = (((Dx_0.^2)+(Dy_0.^2)+(Dz_0.^2)).^(1/2));   % |grad phi|
end

if(method == 'Explicit')
    % CURVATURE:   *mu*k|grad phi|*   (central differences):
    K = zeros(M,N,P);

    Dxy = (phi_xp_yp - phi_xp_ym - phi_xm_yp + phi_xm_ym) / (4*dx*dy);
    Dxz = (phi_xp_zp - phi_xp_zm - phi_xm_zp + phi_xm_zm) / (4*dx*dz);
    Dyz = (phi_yp_zp - phi_yp_zm - phi_ym_zp + phi_ym_zm) / (4*dy*dz);

    K = ( (Dx_0.^2).*Dyy - 2*Dx_0.*Dy_0.*Dxy + (Dy_0.^2).*Dxx ...
        + (Dx_0.^2).*Dzz - 2*Dx_0.*Dz_0.*Dxz + (Dz_0.^2).*Dxx ... 
        + (Dy_0.^2).*Dzz - 2*Dy_0.*Dz_0.*Dyz + (Dz_0.^2).*Dyy) ./ ((Dx_0.^2 + Dy_0.^2 + Dz_0.^2).^(3/2) + epsilon);

    phi_temp = phi + dt * Grad .* ( mu.*K + lambda1*(u0 - c1).^2 - lambda2*(u0 - c2).^2 );

elseif(method == 'Implicit')
    C1x = 1 ./ sqrt(Dx_p.^2 + Dy_0.^2 + Dz_0.^2 + (10e-7)^2);
    C2x = 1 ./ sqrt(Dx_m.^2 + Dy_0.^2 + Dz_0.^2 + (10e-7)^2);
    C3y = 1 ./ sqrt(Dx_0.^2 + Dy_p.^2 + Dz_0.^2 + (10e-7)^2);
    C4y = 1 ./ sqrt(Dx_0.^2 + Dy_m.^2 + Dz_0.^2 + (10e-7)^2);
    C5z = 1 ./ sqrt(Dx_0.^2 + Dy_0.^2 + Dz_p.^2 + (10e-7)^2);
    C6z = 1 ./ sqrt(Dx_0.^2 + Dy_0.^2 + Dz_m.^2 + (10e-7)^2);

    % m = (dt/(dx*dy)) * Grad .* mu;        % 2D
    m = (dt/(dx*dy)) * Grad .* mu;
    C = 1 + m.*(C1x + C2x + C3y + C4y + C5z + C6z);

    C1x_2x = C1x.*phi_xp + C2x.*phi_xm;
    C3y_4y = C3y.*phi_yp + C4y.*phi_ym;
    C5z_6z = C5z.*phi_zp + C6z.*phi_zm;

    phi_temp = (1 ./ C) .* ( phi + m.*(C1x_2x+C3y_4y) + (dt*Grad).*(lambda1*(u0 - c1).^2) - (dt*Grad).*(lambda2*(u0 - c2).^2) );
end

phi = phi_temp;

phi_visualize =  permute(phi,[2,1,3]);
write_to_binary_file(phi_visualize,n);     % record

end

time = toc

n = n
T = dt*n

clear
clear all

---

通常，Matlab以矩阵的形式跟踪所有变量。当您处理大量具有多个维度的变量时，将分配RAM内存来存储此变量。因此，在处理将运行多次迭代的大量变量时，最好从内存中清除该变量。要执行此操作，请使用命令

清除变量名称1、变量名称2，。。。变量名称3

虽然保留所有变量可以使代码看起来井然有序，但是当您遇到此类问题时，请尝试清除不需要的变量

---

检查此链接以详细使用clear命令：

这不是一个特别大的矩阵，前提是您还没有使用32位操作系统或只有一点RAM。如果您向我们展示有问题的代码，我们可能会提供帮助。更好的是，花一点时间创建一个仍能说明问题的模型。嗨，我已经发布了代码。它用于3D数据的分割。你知道为什么它不能很好地处理大量数据吗？那里发生了很多事情。你的代码无法运行，所以我帮不了你什么忙。在大

for

循环中，我看不到任何正在增长或未预分配的内容（

u0\u顶部的颜色

不是–有多大？）。您正在运行多少次迭代？代码中何时何地出现问题？在什么迭代中？开始调试并打印变量。尝试使用（

profview

是GUI界面，但您可能希望使用

profile

）。