function A = mtimes(B,C) % --*-- Unitary tests --*--

%@info:
%! @deftypefn {Function File} {@var{A} =} mtimes (@var{B},@var{C})
%! @anchor{@dseries/mtimes}
%! @sp 1
%! Overloads the mtimes 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) 2012-2013 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 <http://www.gnu.org/licenses/>.

if isdseries(B) && isdseries(C)
    % Element by element multiplication of two dseries object
    if ~isequal(B.vobs,C.vobs) && ~(isequal(B.vobs,1) || isequal(C.vobs,1))
        error(['dseries::times: Cannot multiply ' 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.vobs<C.vobs
            idB = ones(1,C.vobs);
            idC = 1:C.vobs;
        else
            idB = 1:B.vobs;
            idC = 1:C.vobs;
        end
    end
    if ~isequal(B.freq,C.freq)
        error(['dseries::times: Cannot multiply ' inputname(1) ' and ' inputname(2) ' (frequencies are different)!'])
    end
    if ~isequal(B.nobs,C.nobs) || ~isequal(B.init,C.init)
        [B, C] = align(B, C);
    end
    A = dseries();
    A.freq = B.freq;
    A.init = B.init;
    A.dates = B.dates;
    A.nobs = max(B.nobs,C.nobs);
    A.vobs = max(B.vobs,C.vobs);
    A.name = cell(A.vobs,1);
    A.tex = cell(A.vobs,1);
    for i=1:A.vobs
        A.name(i) = {['multiply(' B.name{idB(i)} ',' C.name{idC(i)} ')']};
        A.tex(i) = {['(' B.tex{idB(i)} '*' C.tex{idC(i)} ')']};
    end
    A.data = bsxfun(@times,B.data,C.data);
elseif isnumeric(C) &&  isreal(C) && isequal(length(C),1) && isdseries(B)
    % Multiplication of a dseries object by a real scalar.
    A = dseries();
    A.freq = B.freq;
    A.init = B.init;
    A.dates = B.dates;
    A.nobs = B.nobs;
    A.vobs = B.vobs;
    A.name = cell(A.vobs,1);
    A.tex = cell(A.vobs,1);
    for i=1:A.vobs
        A.name(i) = {['multiply(' B.name{i} ',' num2str(C) ')']};
        A.tex(i) = {['(' B.tex{i} '*' num2str(C) ')']};
    end
    A.data = B.data*C;    
elseif isnumeric(B) && isreal(B) && isequal(length(B),1) && isdseries(C)
    % Multiplication of a dseries object by a real scalar.
    A = dseries();
    A.freq = C.freq;
    A.init = C.init;
    A.dates = C.dates;
    A.nobs = C.nobs;
    A.vobs = C.vobs;
    A.name = cell(A.vobs,1);
    A.tex = cell(A.vobs,1);
    for i=1:A.vobs
        A.name(i) = {['multiply(' num2str(B) ',' C.name{i} ')']};
        A.tex(i) = {['(' num2str(B) '*'  C.tex{i} ')']};
    end
    A.data = C.data*B;
else
    error()
end

%@test:1
%$ % Define a datasets.
%$ A = rand(10,2); B = randn(10,1);
%$
%$ % Define names
%$ A_name = {'A1';'A2'}; B_name = {'B1'};
%$
%$
%$ % Instantiate a time series object.
%$ try
%$    ts1 = dseries(A,[],A_name,[]);
%$    ts2 = dseries(B,[],B_name,[]);
%$    ts3 = ts1*ts2;
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ if t(1)
%$    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,{'multiply(A1,B1)';'multiply(A2,B1)'});
%$ end
%$ T = all(t);
%@eof:1

%@test:2
%$ % Define a datasets.
%$ A = rand(10,2); B = pi;
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$
%$ % Instantiate a time series object.
%$ try
%$    ts1 = dseries(A,[],A_name,[]);
%$    ts2 = ts1*B;
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ if t(1)
%$    t(2) = dyn_assert(ts2.vobs,2);
%$    t(3) = dyn_assert(ts2.nobs,10);
%$    t(4) = dyn_assert(ts2.data,A*B,1e-15);
%$    t(5) = dyn_assert(ts2.name,{['multiply(A1,' num2str(pi) ')'];['multiply(A2,' num2str(pi) ')']});
%$ end
%$ T = all(t);
%@eof:2

%@test:3
%$ % Define a datasets.
%$ A = rand(10,2); B = pi;
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$
%$ % Instantiate a time series object.
%$ try
%$    ts1 = dseries(A,[],A_name,[]);
%$    ts2 = B*ts1;
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ if t(1)
%$    t(2) = dyn_assert(ts2.vobs,2);
%$    t(3) = dyn_assert(ts2.nobs,10);
%$    t(4) = dyn_assert(ts2.data,A*B,1e-15);
%$    t(5) = dyn_assert(ts2.name,{['multiply(' num2str(pi) ',A1)'];['multiply(' num2str(pi) ',A2)']});
%$ end
%$ T = all(t);
%@eof:3