row indices of an array which is a subset of another array
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Eg. b is a matrix of size(17,2). (BIG MATRIX)
b(:,1)= [ 7;6;5;4;4;3;2;1;20;19;18;17;16;20;21;22;23]
b(:,2) = [30;29;28;27;8;9;10;11;8;12;13;14;15;27;26;25;24]
Now, I need the row indices from this array b which has matching entries in a vector a. The size of vector a is smaller than b. But if the indices are repeated, I want the neighboring row entry.
What I mean by neighboring row entry?
lets say a is : [4; 3; 2; 1]. The entries of a will either be in b(:,1) or b(:,2). there would surely not be any intersection. When I search for a in b(:,1) or (b(:,2)), i will get the row indices [5; 6; 7; 8]. (These are the row indices.) When I search for a = [20;21;22;23] in b(:,1), I want it to return the row indices as [14 15 16 17]..
When a is : [7;6;5;4], I want the row indices [1 2 3 4].
"ismember" allows me to return the first or the last row entries. My requirement here is a bit different.
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Jan
2017년 12월 27일
편집: Jan
2017년 12월 28일
Maybe your mean:
b = cat(2, [ 7;6;5;4;4;3;2;1;20;19;18;17;16;20;21;22;23], ...
[30;29;28;27;8;9;10;11;8;12;13;14;15;27;26;25;24]);
a = [20; 21; 22; 23];
[~, Result] = ismember(a, b(:, 1), 'legacy');
if ~any(Result)
[~, Result] = ismember(a, b(:, 2), 'legacy');
end
But I detest the 'legacy' flag. Even the documentation is vague about its meaning:
preserves the behavior of the ismember function from R2012b and prior
releases using any of the input arguments in previous syntaxes.
Without knowing what the prior (to what?!) releases did, this description is useless. There is no way to let unique search for 'stable' and 'last' at the same time.
Therefore I'd prefer:
b = cat(2, [ 7;6;5;4;4;3;2;1;20;19;18;17;16;20;21;22;23], ...
[30;29;28;27;8;9;10;11;8;12;13;14;15;27;26;25;24]);
[B1, Index1] = uniqueStableLast(b);
[B2, Index2] = uniqueStableLast(b);
[~, loc] = ismember(a, B1);
if any(loc)
Result = Index1(loc);
else
[~, loc] = ismember(a, B2);
Result = Index2(loc);
end
With:
function [B, AI, BI] = uniqueStableLast(A)
nA = numel(A);
if nA
% Stable with choosing the last element:
[As, SV] = sort(A(:), 'descend');
As = As(nA:-1:1);
SV = SV(nA:-1:1);
% Stable with the first element would be:
% [As, SV] = sort(A(:));
if nargout == 1
UV(SV) = [false; diff(As) ~= 0];
B = A(UV);
else % Indices requested:
UV = [false; diff(As)] ~= 0];
UVs(SV) = UV;
AI = find(UVs);
B = A(UVs);
if nargout == 3
% Complex creation of BI such that BB(BI) == A:
v = zeros(1, nA);
v(AI) = 1:length(AI); % Sequence related to BB
vs = v(SV); % Sorted like A
vf = vs(vs ~= 0); % Just the filled entries
BI(SV) = vf(cumsum(UV)); % Inflate multiple elements
end
end
else
B = [];
AI = [];
BI = [];
end
By the way: This is even faster than Matlab's unique('stable').
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