144 lines
3.6 KiB
Matlab
144 lines
3.6 KiB
Matlab
function a = vertcat(varargin) % --*-- Unitary tests --*--
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%@info:
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%! @deftypefn {Function file} {@var{a} =} vertcat (@var{b},@var{c}, ...)
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%! @anchor{horzcat}
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%! @sp 1
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%! Method of the dseries class.
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%! @sp 1
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%! This method overloads the vertical concatenation operator, so that
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%! two (or more) time series objects containing the same variables
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%! can be merged using the following syntax:
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%!
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%! a = [b; c; d];
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%! @sp 2
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%! @strong{Inputs}
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%! @sp 1
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%! @table @ @var
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%! @item b
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%! Dynare time series object, instantiated by @ref{dseries}.
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%! @item c
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%! Dynare time series object, instantiated by @ref{dseries}.
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%! @end table
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%! @sp 2
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%! @strong{Outputs}
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%! @sp 1
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%! @table @var
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%! @item a
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%! Dynare time series object.
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%! @end table
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%! @end deftypefn
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%@eod:
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% Copyright (C) 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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if nargin==0
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a = DynSeries();
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elseif nargin == 1
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a = varargin{1};
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elseif nargin>1
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a = varargin{1};
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for i=2:nargin
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a = vertcat_(a,varargin{i});
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end
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end
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function d = vertcat_(b, c)
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d = NaN;
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if ~isequal(b.freq, c.freq)
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error('dseries::vertcat: Frequencies must be common!')
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end
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if ~isequal(b.vobs, c.vobs)
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error('dseries::vertcat: Number of variables must be common!')
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end
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if ~isequal(b.name, c.name)
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error('dseries::vertcat: Variables must be common!')
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end
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d = b;
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d.data = [b.data; c.data];
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d.dates = [b.dates; c.dates];
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d.nobs = b.nobs+c.nobs;
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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 = {'A1';'A2'};
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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'};
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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(5) = dyn_assert(ts3.nobs,20);
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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(1:10),2*transpose(1:10)];
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%$ C = [transpose(1:10),3*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 = {'A1';'A2'};
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%$ C_name = {'A1';'A2'};
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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'};
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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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%$
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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(5) = dyn_assert(ts4.nobs,30);
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%$ T = all(t);
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%@eof:2
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