wehub-resource-sync
64 lines
1.5 KiB
Matlab
Executable File
64 lines
1.5 KiB
Matlab
Executable File
% Class for Gaussian distribution used by Dirichlet process
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classdef Gauss
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properties
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n_
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mu_
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U_
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end
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methods
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function obj = Gauss(X)
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n = size(X,2);
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mu = mean(X,2);
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U = chol(X*X');
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obj.n_ = n;
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obj.mu_ = mu;
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obj.U_ = U;
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end
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function obj = clone(obj)
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end
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function obj = addSample(obj, x)
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n = obj.n_;
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mu = obj.mu_;
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U = obj.U_;
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n = n+1;
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mu = mu+(x-mu)/n;
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U = cholupdate(U,x,'+');
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obj.n_ = n;
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obj.mu_ = mu;
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obj.U_ = U;
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end
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function obj = delSample(obj, x)
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n = obj.n_;
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mu = obj.mu_;
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U = obj.U_;
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n = n-1;
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mu = mu-(x-mu)/n;
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U = cholupdate(U,x,'-');
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obj.n_ = n;
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obj.mu_ = mu;
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obj.U_ = U;
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end
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function y = logPdf(obj,X)
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n = obj.n_;
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mu = obj.mu_;
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U = obj.U_;
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d = size(X,1);
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U = cholupdate(U/sqrt(n),mu,'-'); % Sigma=X*X'/n-mu*mu'
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Q = U'\bsxfun(@minus,X,mu);
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q = dot(Q,Q,1); % quadratic term (M distance)
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c = d*log(2*pi)+2*sum(log(diag(U))); % normalization constant
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y = -0.5*(c+q);
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end
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end
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end |