getInstanceWeights.m

function [thetaVals, instanceWeightsInEachBag] = getInstanceWeights(kernelWeights, allSeqsTransformationKernel)

% GETINSTANCEWEIGHTS
% Computes the theta values and instance weights from the sub-kernel weights and segment 
% transformations
% 
% INPUT PARAMS
% Param 'kernelWeights'
% Weights assigned by MKL tf each of the sub-kernels in the collection
%
% Param 'allSeqsTransformationKernel'
% Per sequence transformation of segments used to compute the instance weights
%
% OUTPUT PARAMS
% Param 'thetaVals'
% The theta values corresponding to each cluster centre 
% 
% Param 'instanceWeightsInEachBag'
% Weight for each segment per sequence
%
% ADDITIONAL NOTES
% -- Theta vals and sub-kernel weights follow a squared relation (Refer paper)
% 
% -- Order followed is: 
%    . non-shifted kernels (1 to N) first, then shifted kernels (N+1 to 2N) in total 2N kernels
%
% -- Number of kernels is same as number of clusters
%
%
% Author: snikumbh@mpi-inf.mpg.de

thetaVals = sqrt(kernelWeights);
thetaVals = thetaVals';
nBags = size(allSeqsTransformationKernel,2);
nKernels = size(kernelWeights,1);

for j=1:nBags
    instanceWeightsInEachBag{j} = zeros(size(allSeqsTransformationKernel{j},1) , 1);
end
% compute instance weights for instances in each bag
% 
for j=1:nBags
    temp = sum(repmat(thetaVals(1, 1 : nKernels ), ...
		size(allSeqsTransformationKernel{j},1), 1) ...
                .* allSeqsTransformationKernel{j}, 2);
    instanceWeightsInEachBag{j} = temp;
    % if to be written to file, pass fname to the function
    % stdTemp = standardizeMatrix(temp');
    % finalTemp = zeros(size(stdTemp));
    % Using rankings
    % [~, ranking] = sort(stdTemp(1:size(stdTemp,1),1:size(stdTemp,2)), 2, 'descend');
    % finalTemp(1,ranking) = 1:size(stdTemp,2);
    % dlmwrite(fname, finalTemp, '-append');
end



end