我正在尝试将一些代码从Matlab转换为Python，但我对Matlab的语法和功能相当不熟悉。我已经设法使用PIL和Numpy python包完成了一些转换，但我希望有人能够解释一下此代码的一些元素是怎么回事。

clear all;close all;clc;

% Set gray scale to 0 for color images. Will need more memory
GRAY_SCALE = 1

% The physical mask placed close to the sensor has 4 harmonics, therefore
% we will have 9 angular samples in the light field
nAngles = 9;
cAngles = (nAngles+1)/2;

% The fundamental frequency of the cosine in the mask in pixels
F1Y = 238;  F1X = 191;  %Cosine Frequency in Pixels from Calibration Image
F12X = floor(F1X/2);
F12Y = floor(F1Y/2);

%PhaseShift due to Mask In-Plane Translation wrt Sensor
phi1 = 300;  phi2 = 150;

%read 2D image
disp('Reading Input Image...');
I = double(imread('InputCones.png'));

if(GRAY_SCALE)
   %take green channel only
   I = I(:,:,2);
end

%make image odd size
I = I(1:end,1:end-1,:);

%find size of image
[m,n,CH] = size(I);

%Compute Spectral Tile Centers, Peak Strengths and Phase
for i = 1:nAngles
    for j = 1:nAngles
        CentY(i,j) = (m+1)/2 + (i-cAngles)*F1Y;
        CentX(i,j) = (n+1)/2 + (j-cAngles)*F1X;
        %Mat(i,j) = exp(-sqrt(-1)*((phi1*pi/180)*(i-cAngles) + (phi2*pi/180)*(j-cAngles)));
    end
end

Mat = ones(nAngles,nAngles);
% 20 is because we cannot have negative values in the mask. So strenght of
% DC component is 20 times that of harmonics
Mat(cAngles,cAngles) = Mat(cAngles,cAngles) * 20;

% Beginning of 4D light field computation
% do for all color channel

for ch = 1:CH

    disp('=================================');
    disp(sprintf('Processing channel %d',ch));

    % Find FFT of image
    disp('Computing FFT of 2D image');
    f = fftshift(fft2(I(:,:,ch)));

    %If you want to visaulize the FFT of input 2D image (Figure 8 of
    %paper), uncomment the next 2 lines
    %     figure;imshow(log10(abs(f)),[]);colormap gray;
    %     title('2D FFT of captured image (Figure 8 of paper). Note the spectral     replicas');

    %Rearrange Tiles of 2D FFT into 4D Planes to obtain FFT of 4D Light-Field
    disp('Rearranging 2D FFT into 4D');
    for i = 1: nAngles
        for j = 1: nAngles
            FFT_LF(:,:,i,j) =  f( CentY(i,j)-F12Y:CentY(i,j)+F12Y, CentX(i,j)-F12X:CentX(i,j)+F12X)/Mat(i,j);
        end
    end
    clear f

    k = sqrt(-1);
    for i = 1:nAngles
        for j = 1:nAngles
            shift = (phi1*pi/180)*(i-cAngles) + (phi2*pi/180)*(j-cAngles);
            FFT_LF(:,:,i,j) = FFT_LF(:,:,i,j)*exp(k*shift);
        end
    end


    disp('Computing inverse 4D FFT');
    LF     =    ifftn(ifftshift(FFT_LF)); %Compute Light-Field by 4D Inverse FFT
    clear FFT_LF

    if(ch==1)
        LF_R = LF;
    elseif(ch==2)
        LF_G = LF;
    elseif(ch==3)
        LF_B = LF;
    end
    clear LF

end
clear I

%Now we have 4D light fiel

disp('Light Field Computed. Done...');
disp('==========================================');



% Digital Refocusing Code
% Take a 2D slice of 4D light field
% For refocusing, we only need the FFT of light field, not the light field

disp('Synthesizing Refocused Images by taking 2D slice of 4D Light Field');

if(GRAY_SCALE)
    FFT_LF_R = fftshift(fftn(LF_R));
    clear LF_R
else
    FFT_LF_R = fftshift(fftn(LF_R));
    clear LF_R

    FFT_LF_G = fftshift(fftn(LF_G));
    clear LF_G

    FFT_LF_B = fftshift(fftn(LF_B));
    clear LF_B
end

% height and width of refocused image
H = size(FFT_LF_R,1);
W = size(FFT_LF_R,2);

count = 0;
for theta = -14:14

    count = count + 1;

    disp('===============================================');
    disp(sprintf('Calculating New ReFocused Image: theta = %d',theta));

    if(GRAY_SCALE)
        RefocusedImage = Refocus2D(FFT_LF_R,[theta,theta]);
    else
        RefocusedImage = zeros(H,W,3);
        RefocusedImage(:,:,1) = Refocus2D(FFT_LF_R,[theta,theta]);
        RefocusedImage(:,:,2) = Refocus2D(FFT_LF_G,[theta,theta]);
        RefocusedImage(:,:,3) = Refocus2D(FFT_LF_B,[theta,theta]);
    end

    str = sprintf('RefocusedImage%03d.png',count);

    %Scale RefocusedImage in [0,255]
    RefocusedImage = RefocusedImage - min(RefocusedImage(:));
    RefocusedImage = 255*RefocusedImage/max(RefocusedImage(:));

    %write as png image
    clear tt
    for ii = 1:CH
        tt(:,:,ii) = fliplr(RefocusedImage(:,:,ii)');
    end
    imwrite(uint8(tt),str);

    disp(sprintf('Refocused image written as %s',str));

end

下面是重聚焦2d函数：

function IOut = Refocus2D(FFTLF,theta)

[m,n,p,q] = size(FFTLF);
Theta1 = theta(1);
Theta2 = theta(2);

cTem = floor(size(FFTLF)/2)  +   1;

% find the coordinates of 2D slice
[XX,YY] = meshgrid(1:n,1:m);
cc = (XX - cTem(2))/size(FFTLF,2);
cc = Theta2*cc + cTem(4);
dd = (YY - cTem(1))/size(FFTLF,1);
dd = Theta1*dd + cTem(3);

% Resample 4D light field along the 2D slice
v = interpn(FFTLF,YY,XX,dd,cc,'cubic');

%set nan values to zero
idx = find(isnan(v)==1);
disp(sprintf('Number of Nans in sampling = %d',size(idx,1)))
v(isnan(v)) =   0;

% take inverse 2D FFT to get the image
IOut = real(ifft2(ifftshift(v)));

如果有人能帮忙，我将不胜感激。
先谢了
抱歉：下面是代码的简要描述：
该代码读取光场的图像，并且利用全光掩模的先验知识，我们存储掩模的相关nAngle和基频以及相移，这些用于找到图像的多个光谱副本。
读入图像并提取绿色通道后，我们对图像执行快速傅立叶变换，并开始从图像矩阵中获取代表光谱副本之一的切片。
然后，我们对所有光谱副本进行傅立叶逆变换，以产生光场。
然后，重新聚焦2d功能获取4d数据的2维切片，以重新创建重新聚焦的图像。
我特别纠结的事情是：

FFT_LF(:,:,i,j) =  f( CentY(i,j)-F12Y:CentY(i,j)+F12Y, CentX(i,j)-F12X:CentX(i,j)+F12X)/Mat(i,j);

型
我们从矩阵f中取一个切片，但是FFT_LF中的数据在哪里？（：，：，i，j）是什么意思？它是多维数组吗？
那么size函数返回什么

[m,n,p,q] = size(FFTLF);

只要简单解释一下如何将其翻译成python就会有很大的帮助。
到目前为止感谢大家：）