Dynamic-Calibration/utils/YALMIP-master/extras/@ncvar/minus.m

223 lines
6.4 KiB
Matlab
Executable File

function y = minus(X,Y)
%MINUS (overloaded)
% Make sure we can manipulate objects on low-level
if isa(X,'sdpvar')
X = ncvar(X);
elseif isa(Y,'sdpvar')
Y = ncvar(Y);
end
X_is_ncvar = isa(X,'ncvar');
Y_is_ncvar = isa(Y,'ncvar');
switch 2*X_is_ncvar+Y_is_ncvar
case 1
if isempty(X)
try
y = full(X - reshape(Y.basis(:,1),Y.dim(1),Y.dim(2)));
catch
error(lasterr);
end
return
end
y = Y;
n_Y = Y.dim(1);
m_Y = Y.dim(2);
[n_X,m_X] = size(X);
x_isscalar = (n_X*m_X==1);
y_isscalar = (n_Y*m_Y==1);
any_scalar = x_isscalar | y_isscalar;
% Speeeeeeed
if x_isscalar & y_isscalar
y.basis = -y.basis;
y.basis(1) = y.basis(1)+X;
% Reset info about conic terms
y.conicinfo = [0 0];
return
end
if any_scalar | ([n_Y m_Y]==[n_X m_X])
if y_isscalar
y.basis = repmat(y.basis,n_X*m_X,1);
y.dim(1) = n_X;
y.dim(2) = m_X;
end
y.basis = -y.basis;
if nnz(X)~=0
y.basis(:,1) = y.basis(:,1)+X(:);
end
else
error('Matrix dimensions must agree.');
end
% Reset info about conic terms
y.conicinfo = [0 0];
case 2
if isempty(Y)
try
y = full(reshape(X.basis(:,1),X.dim(1),X.dim(2))-Y);
catch
error(lasterr);
end
return
end
y = X;
n_X = X.dim(1);
m_X = X.dim(2);
[n_Y,m_Y] = size(Y);
x_isscalar = (n_X*m_X==1);
y_isscalar = (n_Y*m_Y==1);
any_scalar = x_isscalar | y_isscalar;
% Silly hack
% Taking X-scalar(0) takes unnecessary time
% and is used in most definitions of LMIs
if (y_isscalar & (Y==0))
return
end
% Speeeeeeed
if x_isscalar & y_isscalar
y.basis(1) = y.basis(1)-Y;
% Reset info about conic terms
y.conicinfo = [0 0];
return
end
if any_scalar | ([n_Y m_Y]==[n_X m_X])
if x_isscalar
y.basis = repmat(y.basis,n_Y*m_Y,1);
y.dim(1) = n_Y;
y.dim(2) = m_Y;
end
y.basis(:,1) = y.basis(:,1)-Y(:);
else
error('Matrix dimensions must agree.');
end
% Update information about conic terms
% This information is used in DUALIZE to
% speed up some checks, and to facilitate some
% advanced dualization features. It also
% speeds up checking for symmetry in some other code
% Ugly, but the best way at the moment
% For a description of this field, check SDPVAR code
% if (y.conicinfo(1)~=0) & isequal(Y,Y') & (y.conicinfo(2) ~= 2)
% y.conicinfo(2) = max(1,y.conicinfo(2));
% else
y.conicinfo = [0 0];
% end
case 3
% if (X.typeflag~=0) | (Y.typeflag~=0)
% error('Relational objects cannot be manipulated')
% end
n_X = X.dim(1);
m_X = X.dim(2);
n_Y = Y.dim(1);
m_Y = Y.dim(2);
x_isscalar = (n_X*m_X==1);
y_isscalar = (n_Y*m_Y==1);
any_scalar = x_isscalar | y_isscalar;
if ~any_scalar
if (~((n_X==n_Y) & (m_X==m_Y)))
error('Matrix dimensions must agree.')
end
end
all_lmi_variables = uniquestripped([X.lmi_variables Y.lmi_variables]);
y = X;
X.basis = []; % Returns memory?
y.lmi_variables = all_lmi_variables;
in_X_logical = ismembc(all_lmi_variables,X.lmi_variables);
in_Y_logical = ismembc(all_lmi_variables,Y.lmi_variables);
in_X = find(in_X_logical);
in_Y = find(in_Y_logical);
if isequal(X.lmi_variables,Y.lmi_variables) & n_Y==n_X & m_Y==m_X
y.basis = y.basis - Y.basis;
% Super special case f(scalar)-f(scalar)
if length(X.lmi_variables)==1
if all(y.basis(:,2)==0)
y = full(y.basis(1));
else
y.conicinfo = [0 0];
end
return
end
else
if 1
[ix,jx,sx] = find(y.basis);y.basis = [];
[iy,jy,sy] = find(Y.basis);Y.basis = [];
mapX = [1 1+in_X];
mapY = [1 1+in_Y];
basis_X = sparse(ix,mapX(jx),sx,n_X*m_X,1+length(all_lmi_variables));ix=[];jx=[];sx=[];
basis_Y = sparse(iy,mapY(jy),sy,n_Y*m_Y,1+length(all_lmi_variables));iy=[];jy=[];sy=[];
else
% MATLAB sparse fails on this for huge problems at a certain size
basis_X = spalloc(n_X*m_X,1+length(all_lmi_variables),nnz(X.basis));
basis_Y = spalloc(n_Y*m_Y,1+length(all_lmi_variables),nnz(Y.basis));
basis_X(:,[1 1+in_X])=y.basis;y.basis = [];
basis_Y(:,[1 1+in_Y])=Y.basis;Y.basis = [];
end
% Fix addition of matrix+scalar
if n_X*m_X<n_Y*m_Y
y.dim(1) = n_Y;
y.dim(2) = m_Y;
basis_X = repmat(basis_X,n_Y*m_Y,1);
end
if n_Y*m_Y<n_X*m_X
y.dim(1) = n_X;
y.dim(2) = m_X;
basis_Y = repmat(basis_Y,n_X*m_X,1);
end
% OK, solution is...
y.basis = basis_X - basis_Y;
end
% Only clean if there are variables used in both
%if ~all(xor(in_X_logical,in_Y_logical))
% Reset info about conic terms
% if (y.conicinfo(1)~=0) & ishermitian(Y) & isempty(intersect(X.lmi_variables,Y.lmi_variables))
% y.conicinfo = [y.conicinfo(2);
% else
y.conicinfo = [0 0];
% end
y = clean(y);
%else
%end
otherwise
end
% Update info on KYP objects
if X_is_ncvar & Y_is_ncvar & X.typeflag==9 & Y.typeflag==9
error('Substraction of KYP objects currently not supported')
end
if Y_is_ncvar & Y.typeflag==9
y.extra.M = -Y.extra.M+X;
y.extra.negated = ~Y.extra.negated;
return
end
if X_is_ncvar & X.typeflag==9
y.extra.M = y.extra.M-Y;
return
end