292 lines
7.1 KiB
Matlab
292 lines
7.1 KiB
Matlab
function B = horzcat(varargin) % --*-- Unitary tests --*--
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% Overloads horzcat method for dseries objects.
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%
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% INPUTS
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% o A1 dseries object.
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% o A2 dseries object.
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% o ...
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%
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% OUTPUTS
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% o B dseries object.
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%
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% EXAMPLE 1
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% If A, B and C are dseries objects the following syntax:
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%
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% D = [A, B, C] ;
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%
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% Defines a dseries object D containing the variables appearing in A, B and C.
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%
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% REMARKS
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% o A1, A2, ... must not have common variables.
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% Copyright (C) 2011-2013 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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switch nargin
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case 0
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B = dseries();
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case 1
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B = varargin{1};
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otherwise
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B = concatenate(varargin{1}, varargin{2});
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if nargin>2
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B = horzcat(B, varargin{3:end});
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end
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end
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function a = concatenate(b,c)
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[n,message] = common_strings_in_cell_arrays(b.name,c.name);
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if n
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error(['dseries::horzcat: I cannot concatenate dseries objects with common variable names (' message ')!'])
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end
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if ~isequal(b.freq,c.freq)
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error('dseries::horzcat: All time series objects must have common frequency!')
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else
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a = dseries();
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a.freq = b.freq;
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end
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d_nobs_flag = 0;
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if ~isequal(b.nobs,c.nobs)
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d_nobs_flag = 1;
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else
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a.nobs = b.nobs;
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end
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d_init_flag = 0;
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if ~isequal(b.init,c.init)
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d_init_flag = 1;
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end
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a.vobs = b.vobs+c.vobs;
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a.name = vertcat(b.name,c.name);
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a.tex = vertcat(b.tex,c.tex);
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if ~( d_nobs_flag(1) || d_init_flag(1) )
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a.init = b.init;
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a.data = [b.data,c.data];
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a.dates = b.dates;
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else
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if b.init<=c.init
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a.init = b.init;
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if b.init<c.init
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c.data = [NaN(c.init-b.init,c.vobs); c.data];
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end
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else
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a.init = c.init;
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b_first_lines = b.init-c.init;
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b.data = [NaN(b.init-c.init,b.vobs); b.data];
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end
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b_last_date = b.init+b.nobs;
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c_last_date = c.init+c.nobs;
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if b_last_date<c_last_date
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b.data = [b.data; NaN(c_last_date-b_last_date,b.vobs)];
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elseif b_last_date>c_last_date
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c.data = [c.data; NaN(b_last_date-c_last_date,c.vobs)];
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end
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a.data = [b.data, c.data];
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a.dates = unique([b.dates, c.dates]);
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end
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a.nobs = size(a.data,1);
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%@test:1
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),2*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define expected results.
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%$ e.init = dates(1,1);
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [A,B];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,[],A_name,[]);
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%$ ts2 = dseries(B,[],B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$
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%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:1
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%@test:2
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(5:12),2*transpose(5:12)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = 2001;
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%$ B_init = 2005;
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%$
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%$ % Define expected results.
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%$ e.init = dates('2001Y');
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ [A; NaN(2,2)], [NaN(4,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,A_init,A_name,[]);
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%$ ts2 = dseries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:2
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%@test:3
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%$ % Define a data set.
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%$ A = [transpose(1:7),2*transpose(1:7)];
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%$ B = [transpose(5:11),2*transpose(5:11)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = '1950Q1';
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%$ B_init = '1950Q3';
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%$
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%$ % Define expected results.
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%$ e.freq = 4;
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%$ e.init = dates('1950Q1');
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ [A; NaN(2,2)], [NaN(2,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,A_init,A_name,[]);
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%$ ts2 = dseries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:3
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%@test:4
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%$ % Define a data set.
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%$ A = [transpose(1:7),2*transpose(1:7)];
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%$ B = [transpose(5:9),2*transpose(5:9)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = '1950Q1';
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%$ B_init = '1950Q3';
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%$
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%$ % Define expected results.
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%$ e.init = dates(A_init);
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%$ e.freq = 4;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ A, [NaN(2,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,A_init,A_name,[]);
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%$ ts2 = dseries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(isequal(ts3.init,e.init),1);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:4
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%@test:5
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),3*transpose(1:10)];
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%$ C = [transpose(1:10),4*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$ C_name = {'C1';'C2'};
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%$
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%$ % Define expected results.
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%$ e.init = dates(1,1);
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2';'C1';'C2'};
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%$ e.data = [A,B,C];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,[],A_name,[]);
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%$ ts2 = dseries(B,[],B_name,[]);
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%$ ts3 = dseries(C,[],C_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts4 = [ts1,ts2,ts3];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(isequal(ts4.init,e.init),1);
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%$ t(2) = dyn_assert(ts4.freq,e.freq);
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%$ t(3) = dyn_assert(ts4.data,e.data);
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%$ t(4) = dyn_assert(ts4.name,e.name);
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%$ T = all(t);
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%@eof:5
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%@test:6
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),2*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'A2'};
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dseries(A,[],A_name,[]);
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%$ ts2 = dseries(B,[],B_name,[]);
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%$
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%$ % Call the tested method.
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%$ try
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%$ ts3 = [ts1,ts2];
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%$ t = 0;
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%$ catch
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%$ t = 1;
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%$ end
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%$
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%$ T = t;
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%@eof:6
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