function X=pathSolutionLeast(A, y, z, opts)
%
%% Fuction pathSolution:
% Solving the pathwise solutions
%
%% Input & Output parameters
% See the description of the related functions
%
%% Copyright (C) 2009-2010 Jun Liu, and Jieping Ye
%
% You are suggested to first read the Manual.
%
% For any problem, please contact with Jun Liu via j.liu@asu.edu
%
% Last modified 2 August 2009.
%
% Related functions:
% sll_opts, initFactor,
% eppVector, eppMatrix, eplb,
%
% LeastR, LeastC,
% nnLeastR, nnLeastC
% glLeastR, mtLeastR, mcLeastR
%%
switch(opts.fName)
case 'LeastR'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(-z); % sort z in a decresing order
z_value=-z_value; % z_value in a decreasing order
n=size(A,2); % the dimensionality of the data
X=zeros(n,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=LeastR(A, y, z_value(1), opts);
X(:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function LeastR
[x, funVal]=LeastR(A, y, z_value(i), opts);
X(:,z_ind(i))=x; % store the solution
end
case 'LeastC'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(z); % sort z in an ascending order
n=size(A,2); % the dimensionality of the data
X=zeros(n,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=LeastC(A, y, z_value(1), opts);
X(:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function LeastC
[x, funVal]=LeastC(A, y, z_value(i), opts);
X(:,z_ind(i))=x; % store the solution
end
case 'glLeastR'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(-z); % sort z in a decresing order
z_value=-z_value; % z_value in a decreasing order
n=size(A,2); % the dimensionality of the data
X=zeros(n,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=glLeastR(A, y, z_value(1), opts);
X(:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function glLeastR
[x, funVal]=glLeastR(A, y, z_value(i), opts);
X(:,z_ind(i))=x; % store the solution
end
case 'mtLeastR'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(-z); % sort z in a decresing order
z_value=-z_value; % z_value in a decreasing order
n=size(A,2); % the dimensionality of the data
k=length(opts.ind)-1; % the number of tasks
X=zeros(n,k,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=mtLeastR(A, y, z_value(1), opts);
X(:,:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function mtLeastR
[x, funVal]=mtLeastR(A, y, z_value(i), opts);
X(:,:, z_ind(i))=x; % store the solution
end
case 'mcLeastR'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(-z); % sort z in a decresing order
z_value=-z_value; % z_value in a decreasing order
n=size(A,2); % the dimensionality of the data
k=size(y,2); % the number of tasks
X=zeros(n,k,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=mcLeastR(A, y, z_value(1), opts);
X(:,:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=1; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function mcLeastR
[x, funVal]=mcLeastR(A, y, z_value(i), opts);
X(:,:, z_ind(i))=x; % store the solution
end
case 'nnLeastR'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(-z); % sort z in a decresing order
z_value=-z_value; % z_value in a decreasing order
n=size(A,2); % the dimensionality of the data
X=zeros(n,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=nnLeastR(A, y, z_value(1), opts);
X(:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function LeastR
[x, funVal]=nnLeastR(A, y, z_value(i), opts);
X(:,z_ind(i))=x; % store the solution
end
case 'nnLeastC'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(z); % sort z in an ascending order
n=size(A,2); % the dimensionality of the data
X=zeros(n,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=nnLeastC(A, y, z_value(1), opts);
X(:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function LeastC
[x, funVal]=nnLeastC(A, y, z_value(i), opts);
X(:,z_ind(i))=x; % store the solution
end
case 'mtLeastC'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(z); % sort z in an ascending order
n=size(A,2); % the dimensionality of the data
k=length(opts.ind)-1; % the number of tasks
X=zeros(n,k,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=mtLeastC(A, y, z_value(1), opts);
X(:,:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=0; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function mtLeastC
[x, funVal]=mtLeastC(A, y, z_value(i), opts);
X(:,:, z_ind(i))=x; % store the solution
end
case 'mcLeastC'
z_num=length(z); % the number of parameters
[z_value, z_ind]=sort(z); % sort z in an ascending order
n=size(A,2); % the dimensionality of the data
k=size(y,2); % the number of tasks
X=zeros(n,k,z_num); % set the size of output X
% run the code to compute the first solution
[x, funVal]=mcLeastC(A, y, z_value(1), opts);
X(:,:,z_ind(1))=x; % store the solution
% set .init for warm start
opts.init=1; % using .initFactor
for i=2:z_num
opts.x0=x; % warm-start
% run the function mcLeastC
[x, funVal]=mcLeastC(A, y, z_value(i), opts);
X(:,:, z_ind(i))=x; % store the solution
end
otherwise
fprintf('\n The function value specified in opts.fName is not supported!');
end
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