145 lines
3.5 KiB
Matlab
145 lines
3.5 KiB
Matlab
function A = minus(B,C)
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%@info:
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%! @deftypefn {Function File} {@var{A} =} minus (@var{B},@var{C})
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%! @anchor{@dynSeries/minus}
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%! @sp 1
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%! Overloads the minus method for the Dynare time series class (@ref{dynSeries}).
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%! @sp 2
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%! @strong{Inputs}
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%! @sp 1
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%! @table @ @var
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%! @item B
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%! Dynare time series object instantiated by @ref{dynSeries}.
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%! @item C
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%! Dynare time series object instantiated by @ref{dynSeries}.
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%! @end table
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%! @sp 1
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%! @strong{Outputs}
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%! @sp 1
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%! @table @ @var
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%! @item A
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%! Dynare time series object.
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%! @end deftypefn
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%@eod:
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% Copyright (C) 2012-2013 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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if ~isequal(B.vobs,C.vobs) && ~(isequal(B.vobs,1) || isequal(C.vobs,1))
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error(['dynSeries::plus: Cannot substract ' inputname(1) ' and ' inputname(2) ' (wrong number of variables)!'])
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else
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if B.vobs>C.vobs
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idB = 1:B.vobs;
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idC = ones(1:B.vobs);
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elseif B.vobs<C.vobs
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idB = ones(1,C.vobs);
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idC = 1:C.vobs;
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else
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idB = 1:B.vobs;
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idC = 1:C.vobs;
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end
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end
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if ~isequal(B.freq,C.freq)
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error(['dynSeries::plus: Cannot substract ' inputname(1) ' and ' inputname(2) ' (frequencies are different)!'])
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end
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if ~isequal(B.nobs,C.nobs) || ~isequal(B.init,C.init)
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[B, C] = align(B, C);
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end
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if isempty(B)
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A = -C;
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return
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end
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if isempty(C)
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A = B;
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return
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end
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A = dynSeries();
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A.freq = B.freq;
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A.init = B.init;
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A.time = B.time;
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A.nobs = max(B.nobs,C.nobs);
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A.vobs = max(B.vobs,C.vobs);
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A.name = cell(A.vobs,1);
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A.tex = cell(A.vobs,1);
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for i=1:A.vobs
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A.name(i) = {['minus(' B.name{idB(i)} ',' C.name{idC(i)} ')']};
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A.tex(i) = {['(' B.tex{idB(i)} '-' C.tex{idC(i)} ')']};
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end
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A.data = bsxfun(@minus,B.data,C.data);
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%@test:1
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%$ % Define a datasets.
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%$ A = rand(10,2); B = randn(10,1);
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'}; B_name = {'B1'};
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%$
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%$ t = zeros(5,1);
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%$
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%$ % Instantiate a time series object.
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%$ try
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts2 = dynSeries(B,[],B_name,[]);
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%$ ts3 = ts1-ts2;
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%$ t(1) = 1;
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%$ catch
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%$ t = 0;
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%$ end
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%$
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%$ if length(t)>1
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%$ t(2) = dyn_assert(ts3.vobs,2);
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%$ t(3) = dyn_assert(ts3.nobs,10);
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%$ t(4) = dyn_assert(ts3.data,[A(:,1)-B, A(:,2)-B],1e-15);
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%$ t(5) = dyn_assert(ts3.name,{'minus(A1,B1)';'minus(A2,B1)'});
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%$ end
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%$ T = all(t);
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%@eof:1
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%@test:3
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%$ % Define a datasets.
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%$ A = rand(10,2); B = randn(5,1);
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'}; B_name = {'B1'};
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%$
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%$ t = zeros(5,1);
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%$
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%$ % Instantiate a time series object.
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%$ try
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts2 = dynSeries(B,[],B_name,[]);
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%$ ts3 = ts1-ts2;
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%$ t(1) = 1;
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%$ catch
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%$ t = 0;
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%$ end
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%$
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%$ if length(t)>1
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%$ t(2) = dyn_assert(ts3.vobs,2);
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%$ t(3) = dyn_assert(ts3.nobs,10);
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%$ t(4) = dyn_assert(ts3.data,[A(1:5,1)-B(1:5), A(1:5,2)-B(1:5) ; NaN(5,2)],1e-15);
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%$ t(5) = dyn_assert(ts3.name,{'minus(A1,B1)';'minus(A2,B1)'});
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%$ end
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%$ T = all(t);
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%@eof:3
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