function A = plus(B,C) % --*-- Unitary tests --*-- %@info: %! @deftypefn {Function File} {@var{A} =} plus (@var{B},@var{C}) %! @anchor{@dseries/plus} %! @sp 1 %! Overloads the plus method for the Dynare time series class (@ref{dseries}). %! @sp 2 %! @strong{Inputs} %! @sp 1 %! @table @ @var %! @item B %! Dynare time series object instantiated by @ref{dseries}. %! @item C %! Dynare time series object instantiated by @ref{dseries}. %! @end table %! @sp 1 %! @strong{Outputs} %! @sp 1 %! @table @ @var %! @item A %! Dynare time series object. %! @end deftypefn %@eod: % Copyright (C) 2011-2014 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . if isnumeric(B) && (isscalar(B) || isvector(B)) if ~isdseries(C) error('dseries::plus: Second input argument must be a dseries object!') end A = C; A.data = bsxfun(@plus,C.data,B); return; end if isnumeric(C) && (isscalar(C) || isvector(C)) if ~isdseries(B) error('dseries::plus: First input argument must be a dseries object!') end A = B; A.data = bsxfun(@plus,B.data,C); return end if ~isequal(B.vobs,C.vobs) && ~(isequal(B.vobs,1) || isequal(C.vobs,1)) error(['dseries::plus: Cannot add ' inputname(1) ' and ' inputname(2) ' (wrong number of variables)!']) else if B.vobs>C.vobs idB = 1:B.vobs; idC = ones(1,B.vobs); elseif B.vobs1 %$ t(2) = dyn_assert(ts3.vobs,2); %$ t(3) = dyn_assert(ts3.nobs,10); %$ t(4) = dyn_assert(ts3.data,[A(:,1)+B, A(:,2)+B],1e-15); %$ t(5) = dyn_assert(ts3.name,{'plus(A1,B1)';'plus(A2,B1)'}); %$ end %$ T = all(t); %@eof:1 %@test:2 %$ % Define a datasets. %$ A = rand(10,2); B = randn(10,1); %$ %$ % Define names %$ A_name = {'A1';'A2'}; B_name = {'B1'}; %$ %$ t = zeros(5,1); %$ %$ % Instantiate a time series object. %$ try %$ ts1 = dseries(A,[],A_name,[]); %$ ts2 = dseries(B,[],B_name,[]); %$ ts3 = ts1+ts2; %$ ts4 = ts3+ts1; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts4.vobs,2); %$ t(3) = dyn_assert(ts4.nobs,10); %$ t(4) = dyn_assert(ts4.data,[A(:,1)+B, A(:,2)+B]+A,1e-15); %$ t(5) = dyn_assert(ts4.name,{'plus(plus(A1,B1),A1)';'plus(plus(A2,B1),A2)'}); %$ end %$ T = all(t); %@eof:2 %@test:3 %$ % Define a datasets. %$ A = rand(10,2); B = randn(5,1); %$ %$ % Define names %$ A_name = {'A1';'A2'}; B_name = {'B1'}; %$ %$ t = zeros(5,1); %$ %$ % Instantiate a time series object. %$ try %$ ts1 = dseries(A,[],A_name,[]); %$ ts2 = dseries(B,[],B_name,[]); %$ ts3 = ts1+ts2; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts3.vobs,2); %$ t(3) = dyn_assert(ts3.nobs,10); %$ 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); %$ t(5) = dyn_assert(ts3.name,{'plus(A1,B1)';'plus(A2,B1)'}); %$ end %$ T = all(t); %@eof:3 %@test:4 %$ t = zeros(7,1); %$ %$ try %$ ts = dseries(transpose(1:5),'1950q1',{'Output'}, {'Y_t'}); %$ us = dseries(transpose(1:5),'1949q4',{'Consumption'}, {'C_t'}); %$ vs = ts+us; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts.freq,4); %$ t(3) = dyn_assert(us.freq,4); %$ t(4) = dyn_assert(ts.init.time,[1950, 1]); %$ t(5) = dyn_assert(us.init.time,[1949, 4]); %$ t(6) = dyn_assert(vs.init.time,[1949, 4]); %$ t(7) = dyn_assert(vs.nobs,6); %$ end %$ %$ T = all(t); %@eof:4 %@test:5 %$ t = zeros(7,1); %$ %$ try %$ ts = dseries(transpose(1:5),'1950q1',{'Output'}, {'Y_t'}); %$ us = dseries(transpose(1:7),'1950q1',{'Consumption'}, {'C_t'}); %$ vs = ts+us; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts.freq,4); %$ t(3) = dyn_assert(us.freq,4); %$ t(4) = dyn_assert(ts.init.time,[1950, 1]); %$ t(5) = dyn_assert(us.init.time,[1950, 1]); %$ t(6) = dyn_assert(vs.init.time,[1950, 1]); %$ t(7) = dyn_assert(vs.nobs,7); %$ end %$ %$ T = all(t); %@eof:5 %@test:6 %$ t = zeros(8,1); %$ %$ try %$ ts = dseries(transpose(1:5),'1950q1',{'Output'}, {'Y_t'}); %$ us = dseries(transpose(1:7),'1950q1',{'Consumption'}, {'C_t'}); %$ vs = ts+us('1950q1').data; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts.freq,4); %$ t(3) = dyn_assert(us.freq,4); %$ t(4) = dyn_assert(ts.init.time,[1950, 1]); %$ t(5) = dyn_assert(us.init.time,[1950, 1]); %$ t(6) = dyn_assert(vs.init.time,[1950, 1]); %$ t(7) = dyn_assert(vs.nobs,5); %$ t(8) = dyn_assert(vs.data,ts.data+1); %$ end %$ %$ T = all(t); %@eof:6 %@test:7 %$ t = zeros(8,1); %$ %$ try %$ ts = dseries([transpose(1:5), transpose(1:5)],'1950q1'); %$ us = dseries([transpose(1:7),2*transpose(1:7)],'1950q1'); %$ vs = ts+us('1950q1').data; %$ t(1) = 1; %$ catch %$ t = 0; %$ end %$ %$ if length(t)>1 %$ t(2) = dyn_assert(ts.freq,4); %$ t(3) = dyn_assert(us.freq,4); %$ t(4) = dyn_assert(ts.init.time,[1950, 1]); %$ t(5) = dyn_assert(us.init.time,[1950, 1]); %$ t(6) = dyn_assert(vs.init.time,[1950, 1]); %$ t(7) = dyn_assert(vs.nobs,5); %$ t(8) = dyn_assert(vs.data,bsxfun(@plus,ts.data,[1, 2])); %$ end %$ %$ T = all(t); %@eof:7