function B = horzcat(varargin) % --*-- Unitary tests --*--

% Overloads horzcat method for dseries objects.
%
% INPUTS 
%  o A1    dseries object.
%  o A2    dseries object.
%  o ...
%
% OUTPUTS 
%  o B     dseries object.
%
% EXAMPLE 1 
%  If A, B and C are dseries objects the following syntax:
%    
%    D = [A, B, C] ;
%
%  Defines a dseries object D containing the variables appearing in A, B and C.
%
% REMARKS 
%  o A1, A2, ... must not have common variables.
    
% Copyright (C) 2011-2013 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/>.

switch nargin
  case 0
    B = dseries();
  case 1
    B = varargin{1};
  otherwise
    B = concatenate(varargin{1}, varargin{2});
    if nargin>2
        B = horzcat(B, varargin{3:end});
    end
end

function a = concatenate(b,c)
    [n,message] = common_strings_in_cell_arrays(b.name,c.name);
    if n
        error(['dseries::horzcat: I cannot concatenate dseries objects with common variable names (' message ')!'])
    end
    if ~isequal(b.freq,c.freq)
        error('dseries::horzcat: All time series objects must have common frequency!')
    else
        a = dseries();
        a.freq = b.freq;
    end
    d_nobs_flag = 0;
    if ~isequal(b.nobs,c.nobs)
        d_nobs_flag = 1;
    else
        a.nobs = b.nobs;
    end
    d_init_flag = 0;
    if ~isequal(b.init,c.init)
        d_init_flag = 1;
    end
    a.vobs = b.vobs+c.vobs;
    a.name = vertcat(b.name,c.name);
    a.tex  = vertcat(b.tex,c.tex);
    if ~( d_nobs_flag(1) || d_init_flag(1) )
        a.init = b.init;
        a.data = [b.data,c.data];
        a.dates = b.dates;
    else
        if b.init<=c.init
            a.init = b.init;
            if b.init<c.init
                c.data = [NaN(c.init-b.init,c.vobs); c.data];
            end
        else
            a.init = c.init;
            b_first_lines = b.init-c.init;
            b.data = [NaN(b.init-c.init,b.vobs); b.data];
        end
        b_last_date = b.init+b.nobs;
        c_last_date = c.init+c.nobs;
        if b_last_date<c_last_date
            b.data = [b.data; NaN(c_last_date-b_last_date,b.vobs)];
        elseif b_last_date>c_last_date
            c.data = [c.data; NaN(b_last_date-c_last_date,c.vobs)];
        end
        a.data = [b.data, c.data];
        a.dates = unique([b.dates, c.dates]);
    end
    a.nobs = size(a.data,1);

%@test:1
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$ B = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'B2'};
%$
%$ % Define expected results.
%$ e.init = dates(1,1);
%$ e.freq = 1;
%$ e.name = {'A1';'A2';'B1';'B2'};
%$ e.data = [A,B];
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,[],A_name,[]);
%$ ts2 = dseries(B,[],B_name,[]);
%$
%$ % Call the tested method.
%$ ts3 = [ts1,ts2];
%$
%$ % Check the results.
%$
%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
%$ t(2) = dyn_assert(ts3.freq,e.freq);
%$ t(3) = dyn_assert(ts3.data,e.data);
%$ t(4) = dyn_assert(ts3.name,e.name);
%$ T = all(t);
%@eof:1

%@test:2
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$ B = [transpose(5:12),2*transpose(5:12)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'B2'};
%$
%$ % Define initial date
%$ A_init = 2001;
%$ B_init = 2005;
%$
%$ % Define expected results.
%$ e.init = dates('2001Y');
%$ e.freq = 1;
%$ e.name = {'A1';'A2';'B1';'B2'};
%$ e.data = [ [A; NaN(2,2)], [NaN(4,2); B]];
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,A_init,A_name,[]);
%$ ts2 = dseries(B,B_init,B_name,[]);
%$
%$ % Call the tested method.
%$ ts3 = [ts1,ts2];
%$
%$ % Check the results.
%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
%$ t(2) = dyn_assert(ts3.freq,e.freq);
%$ t(3) = dyn_assert(ts3.data,e.data);
%$ t(4) = dyn_assert(ts3.name,e.name);
%$ T = all(t);
%@eof:2

%@test:3
%$ % Define a data set.
%$ A = [transpose(1:7),2*transpose(1:7)];
%$ B = [transpose(5:11),2*transpose(5:11)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'B2'};
%$
%$ % Define initial date
%$ A_init = '1950Q1';
%$ B_init = '1950Q3';
%$
%$ % Define expected results.
%$ e.freq = 4;
%$ e.init = dates('1950Q1');
%$ e.name = {'A1';'A2';'B1';'B2'};
%$ e.data = [ [A; NaN(2,2)], [NaN(2,2); B]];
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,A_init,A_name,[]);
%$ ts2 = dseries(B,B_init,B_name,[]);
%$
%$ % Call the tested method.
%$ ts3 = [ts1,ts2];
%$
%$ % Check the results.
%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
%$ t(2) = dyn_assert(ts3.freq,e.freq);
%$ t(3) = dyn_assert(ts3.data,e.data);
%$ t(4) = dyn_assert(ts3.name,e.name);
%$ T = all(t);
%@eof:3

%@test:4
%$ % Define a data set.
%$ A = [transpose(1:7),2*transpose(1:7)];
%$ B = [transpose(5:9),2*transpose(5:9)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'B2'};
%$
%$ % Define initial date
%$ A_init = '1950Q1';
%$ B_init = '1950Q3';
%$
%$ % Define expected results.
%$ e.init = dates(A_init);
%$ e.freq = 4;
%$ e.name = {'A1';'A2';'B1';'B2'};
%$ e.data = [ A, [NaN(2,2); B]];
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,A_init,A_name,[]);
%$ ts2 = dseries(B,B_init,B_name,[]);
%$
%$ % Call the tested method.
%$ ts3 = [ts1,ts2];
%$
%$ % Check the results.
%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
%$ t(2) = dyn_assert(ts3.freq,e.freq);
%$ t(3) = dyn_assert(ts3.data,e.data);
%$ t(4) = dyn_assert(ts3.name,e.name);
%$ T = all(t);
%@eof:4

%@test:5
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$ B = [transpose(1:10),3*transpose(1:10)];
%$ C = [transpose(1:10),4*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'B2'};
%$ C_name = {'C1';'C2'};
%$
%$ % Define expected results.
%$ e.init = dates(1,1);
%$ e.freq = 1;
%$ e.name = {'A1';'A2';'B1';'B2';'C1';'C2'};
%$ e.data = [A,B,C];
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,[],A_name,[]);
%$ ts2 = dseries(B,[],B_name,[]);
%$ ts3 = dseries(C,[],C_name,[]);
%$
%$ % Call the tested method.
%$ ts4 = [ts1,ts2,ts3];
%$
%$ % Check the results.
%$ t(1) = dyn_assert(isequal(ts4.init,e.init),1);
%$ t(2) = dyn_assert(ts4.freq,e.freq);
%$ t(3) = dyn_assert(ts4.data,e.data);
%$ t(4) = dyn_assert(ts4.name,e.name);
%$ T = all(t);
%@eof:5

%@test:6
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$ B = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$ B_name = {'B1';'A2'};
%$
%$ % Instantiate two time series objects.
%$ ts1 = dseries(A,[],A_name,[]);
%$ ts2 = dseries(B,[],B_name,[]);
%$
%$ % Call the tested method.
%$ try
%$   ts3 = [ts1,ts2];
%$   t = 0;
%$ catch
%$   t = 1;
%$ end
%$
%$ T = t;
%@eof:6