148 lines
3.5 KiB
Matlab
148 lines
3.5 KiB
Matlab
function A = merge(B,C) % --*-- Unitary tests --*--
|
|
|
|
%@info:
|
|
%! @deftypefn {Function File} {@var{A} =} merge (@var{B},@var{C})
|
|
%! @anchor{@dseries/plus}
|
|
%! @sp 1
|
|
%! Overloads the merge 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) 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(C)
|
|
error('dseries::merge: Both inputs must be dseries objects!')
|
|
end
|
|
|
|
if ~isequal(B.freq,C.freq)
|
|
error(['dseries::merge: Cannot merge ' inputname(1) ' and ' inputname(2) ' (frequencies are different)!'])
|
|
end
|
|
|
|
A = dseries();
|
|
A.freq = B.freq;
|
|
[A.name, IBC, junk] = unique([B.name; C.name], 'last');
|
|
tex = [B.tex; C.tex];
|
|
A.tex = tex(IBC);
|
|
A.vobs=length(IBC);
|
|
|
|
if B.nobs == 0
|
|
A = C;
|
|
elseif C.nobs == 0
|
|
A = B;
|
|
elseif B.init >= C.init
|
|
diff = B.init - C.init;
|
|
A.nobs = max(B.nobs + diff, C.nobs);
|
|
A.data = NaN(A.nobs, A.vobs);
|
|
Z1 = [NaN(diff,B.vobs);B.data];
|
|
if A.nobs > B.nobs + diff
|
|
Z1 = [Z1; NaN(A.nobs-(B.nobs + diff),B.vobs)];
|
|
end;
|
|
Z2 = C.data;
|
|
if A.nobs > C.nobs
|
|
Z2 = [Z2; NaN(A.nobs - C.nobs,C.vobs)];
|
|
end;
|
|
Z = [Z1 Z2];
|
|
A.data = Z(:,IBC);
|
|
A.init = C.init;
|
|
else
|
|
diff = C.init - B.init;
|
|
A.nobs = max(C.nobs + diff, B.nobs);
|
|
A.data = NaN(A.nobs, A.vobs);
|
|
Z1 = [NaN(diff,C.vobs);C.data];
|
|
if A.nobs > C.nobs + diff
|
|
Z1 = [Z1; NaN(A.nobs-(C.nobs + diff),C.vobs)];
|
|
end;
|
|
Z2 = B.data;
|
|
if A.nobs > B.nobs
|
|
Z2 = [Z2; NaN(A.nobs - B.nobs,B.vobs)];
|
|
end;
|
|
Z = [Z2 Z1];
|
|
A.data = Z(:,IBC);
|
|
A.init = B.init;
|
|
end
|
|
|
|
A.dates = A.init:A.init+(A.nobs-1);
|
|
|
|
%@test:1
|
|
%$ % Define a datasets.
|
|
%$ A = rand(10,2); B = randn(10,1);
|
|
%$
|
|
%$ % Define names
|
|
%$ A_name = {'A1';'A2'}; B_name = {'A1'};
|
|
%$
|
|
%$ t = zeros(4,1);
|
|
%$
|
|
%$ % Instantiate a time series object.
|
|
%$ try
|
|
%$ ts1 = dseries(A,[],A_name,[]);
|
|
%$ ts2 = dseries(B,[],B_name,[]);
|
|
%$ ts3 = merge(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,[B, A(:,2)],1e-15);
|
|
%$ 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(4,1);
|
|
%$
|
|
%$ % Instantiate a time series object.
|
|
%$ try
|
|
%$ ts1 = dseries(A,[],A_name,[]);
|
|
%$ ts2 = dseries(B,[],B_name,[]);
|
|
%$ ts3 = merge(ts1,ts2);
|
|
%$ t(1) = 1;
|
|
%$ catch
|
|
%$ t = 0;
|
|
%$ end
|
|
%$
|
|
%$ if length(t)>1
|
|
%$ t(2) = dyn_assert(ts3.vobs,3);
|
|
%$ t(3) = dyn_assert(ts3.nobs,10);
|
|
%$ t(4) = dyn_assert(ts3.data,[A, B],1e-15);
|
|
%$ end
|
|
%$ T = all(t);
|
|
%@eof:2 |