考虑以下矩阵:
0 3 0 1 1 4
1 3 5 6 7 0
2 5 6 2 6 1
4 4 2 1 5 1
当我指定元素的位置时,我想获得具有相同值的最近元素的位置。例如,如果我选择第3行第3列中的元素,即' 6&# 39;,我想获得最近的' 6'的行和列值,在这种情况下,它是在第2行第4列。同样,对于' 1&# 39;在第4行,第4列,最近的是在第4行,第5行和第4行,第6行,其中任何一个都很好。我已经查找了' bwdist'和'找到'功能,但他们没有给出正确的结果。任何人都可以帮助我吗?
修改
a1 = randi(10,10,5);
disp(a1);
%// For an array of search numbers
search_array = a1(4,5);
disp(search_array);
%%// Find the linear index of the location
[~,ind] = min(abs(bsxfun(@minus,a1(:),search_array')));%//'
%%// Convert the linear index into row and column numbers
[x,y] = ind2sub(size(a1),ind)
' min'函数在这里不起作用,因为存在所需元素的每个位置将被转换为零并且“#min;' min逐行扫描矩阵并给出第一个零的位置。以下是这种情况:
2 6 10 9 2
6 6 7 5 3
1 8 5 2 1
8 1 9 5 5
9 7 6 4 3
10 6 6 5 3
10 2 7 9 5
6 10 4 5 2
3 6 3 4 5
2 5 6 4 8
即使有一个' 5'就在' 5'旁边在第4行,第5栏,' 5'在第10行,第2列被选中。
答案 0 :(得分:2)
假设A
是输入的二维矩阵,这可能是一种方法 -
%// Row and column indices of the "pivot"
row_id = 4;
col_id = 5;
%// Get the linear index from row and column indices
lin_idx = sub2ind(size(A),row_id,col_id)
%// Logical array with ones at places with same values
search_matches = false(size(A));
search_matches(A==A(lin_idx)) = 1;
%// Create a logical array with just a single 1 at the "pivot"
A_pivot = false(size(A));
A_pivot(lin_idx) = 1;
%// Use BWDIST to find out the distances from the pivot to all the places
%// in the 2D matrix. Set the pivot place and places with non-similar
%// values as Inf, so that later on MIN could be used to find the nearest
%// same values location
distmat = bwdist(A_pivot)
distmat(lin_idx) = Inf
distmat(~search_matches)=Inf
[~,min_lin_idx] = min(distmat(:))
[closest_row_idx,closest_col_idx] = ind2sub(size(A),min_lin_idx)
答案 1 :(得分:2)
此方法不需要任何工具箱。如果不存在具有相同值的其他条目,则返回[]
。
A = [0 3 0 1 1 4
1 3 5 6 7 0
2 5 6 2 6 1
4 4 2 1 5 1]; %// data matrix
pos_row = 3; %// row of reference element
pos_col = 3; %// col of reference element
ref = A(pos_row,pos_col); %// take note of value
A(pos_row,pos_col) = NaN; %// remove it, to avoid finding it as closest
[ii, jj] = find(A==ref); %// find all entries with the same value
A(pos_row,pos_col) = ref; %// restore value
d = (ii-pos_row).^2+ (jj-pos_col).^2; %// compute distances
[~, ind] = min(d); %// find arg min of distances
result_row = ii(ind); %// index with that to obtain result
result_col = jj(ind);