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proj_l1.m
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proj_l1.m
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function op = proj_l1( q, d )
%PROJ_L1 Projection onto the scaled 1-norm ball.
% OP = PROJ_L1( Q ) returns an operator implementing the
% indicator function for the 1-norm ball of radius q,
% { X | norm( X, 1 ) <= q }. Q is optional; if omitted,
% Q=1 is assumed. But if Q is supplied, it must be a positive
% real scalar.
%
% OP = PROJ_L1( Q, D ) uses a scaled 1-norm ball of radius q,
% { X | norm( D.*X, 1 ) <= 1 }. D should be the same size as X
% and non-negative (some zero entries are OK).
%
% Dual: prox_linf.m
% See also: prox_linf, prox_l1, proj_linf
if nargin == 0,
q = 1;
elseif ~isnumeric( q ) || ~isreal( q ) || numel( q ) ~= 1 || q <= 0,
error( 'Argument must be positive.' );
end
if nargin < 2 || isempty(d) || numel(d)==1
if nargin>=2 && ~isempty(d)
% d is a scalar, so norm( d*x ) <= q is same as norm(x)<=q/d
if d==0
error('If d==0 in proj_l1, the set is just {0}, so use proj_0');
elseif d < 0
error('Require d >= 0');
end
q = q/d;
end
op = @(varargin)proj_l1_q(q, varargin{:} );
else
if any(d<0)
error('All entries of d must be non-negative');
end
op = @(varargin)proj_l1_q_d(q, d, varargin{:} );
end
function [ v, x ] = proj_l1_q( q, x, t )
v = 0;
switch nargin,
case 2,
if nargout == 2,
error( 'This function is not differentiable.' );
elseif norm( x(:), 1 ) > q,
v = Inf;
end
case 3,
s = sort(abs(nonzeros(x)),'descend');
cs = cumsum(s);
% ndx = find( cs - (1:numel(s))' .* [ s(2:end) ; 0 ] >= q, 1 );
ndx = find( cs - (1:numel(s))' .* [ s(2:end) ; 0 ] >= q+2*eps(q), 1 ); % For stability
if ~isempty( ndx )
thresh = ( cs(ndx) - q ) / ndx;
x = x .* ( 1 - thresh ./ max( abs(x), thresh ) ); % May divide very small numbers
end
otherwise,
error( 'Not enough arguments.' );
end
% Allows scaling. Added Feb 21 2014
function [ v, x ] = proj_l1_q_d( q, d, x, t )
v = 0;
switch nargin,
case 3,
if nargout == 2,
error( 'This function is not differentiable.' );
elseif norm( d(:).*x(:), 1 ) > q,
v = Inf;
end
case 4,
[lambdas,srt] = sort(abs(nonzeros(x./d)),'descend');
s = abs(x(:).*d(:)); s = s(srt);
dd = d(:).^2; dd= dd(srt);
cs = cumsum(s);
cd = cumsum(dd);
ndx = find( cs - lambdas.*cd >= q+2*eps(q), 1, 'first');
if ~isempty( ndx )
ndx = ndx - 1;
lambda = ( cs(ndx) - q )/cd(ndx);
x = sign(x).*max( 0, abs(x) - lambda*d );
end
otherwise,
error( 'Not enough arguments.' );
end
% TFOCS v1.3 by Stephen Becker, Emmanuel Candes, and Michael Grant.
% Copyright 2013 California Institute of Technology and CVX Research.
% See the file LICENSE for full license information.