You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: piv_FFTensemble.m
    path of file: ./repos/PIVlab
    
    the code of the file until where you have to start completion: function [xtable, ytable, utable, vtable, typevector,correlation_map] = piv_FFTensemble (autolimit,filepath,video_frame_selection,bg_img_A,bg_img_B,clahe,highp,intenscap,clahesize,highpsize,wienerwurst,wienerwurstsize,roi_inpt,converted_mask,interrogationarea,step,subpixfinder,passes,int2,int3,int4,mask_auto,imdeform,repeat,do_pad)
%this funtion performs the  PIV analysis. It is a modification of the
%pivFFTmulti, and will do ensemble correlation. That is a suitable
%algorithm for low seeding density as it happens in microP
    
function [vector] = SUBPIX2DGAUSS(result_conv, interrogationarea, x, y, z, SubPixOffset)
xi = find(~((x <= (size(result_conv,2)-1)) & (y <= (size(result_conv,1)-1)) & (x >= 2) & (y >= 2)));
x(xi) = [];
y(xi) = [];
z(xi) = [];
xmax = size(result_conv, 2);
vector = NaN(size(result_conv,3), 2);
if(numel(x)~=0)
	c10 = zeros(3,3, length(z));
	c01 = c10;
	c11 = c10;
	c20 = c10;
	c02 = c10;
	ip = sub2ind(size(result_conv), y, x, z);

	for i = -1:1
		for j = -1:1
			%following 15 lines based on
			%H. Nobach ï¿½ M. Honkanen (2005)
			%Two-dimensional Gaussian regression for sub-pixel displacement
			%estimation in particle image velocimetry or particle position
			%estimation in particle tracking velocimetry
			%Experiments in Fluids (2005) 38: 511ï¿½515
			c10(j+2,i+2, :) = i*log(result_conv(ip+xmax*i+j));
			c01(j+2,i+2, :) = j*log(result_conv(ip+xmax*i+j));
			c11(j+2,i+2, :) = i*j*log(result_conv(ip+xmax*i+j));
			c20(j+2,i+2, :) = (3*i^2-2)*log(result_conv(ip+xmax*i+j));
			c02(j+2,i+2, :) = (3*j^2-2)*log(result_conv(ip+xmax*i+j));
			%c00(j+2,i+2)=(5-3*i^2-3*j^2)*log(result_conv_norm(maxY+j, maxX+i));
		end