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function us = subsref(ts, S)
%@info:
%! @deftypefn {Function File} {@var{us} =} subsref (@var{ts},S)
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%! @anchor{@dynSeries/subsref}
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%! @sp 1
%! Overloads the subsref method for the Dynare time series class (@ref{dynSeries}).
%! @sp 2
%! @strong{Inputs}
%! @sp 1
%! @table @ @var
%! @item ts
%! Dynare time series object instantiated by @ref{dynSeries}.
%! @item S
%! Matlab's structure array S with two fields, type and subs. The type field is string containing '()', '@{@}', or '.', where '()' specifies
%! integer subscripts, '@{@}' specifies cell array subscripts, and '.' specifies subscripted structure fields. The subs field is a cell array
%! or a string containing the actual subscripts (see matlab's documentation).
%! @end table
%! @sp 1
%! @strong{Outputs}
%! @sp 1
%! @table @ @var
%! @item us
%! Dynare time series object. Depending on the calling sequence @var{us} is a transformation of @var{ts} obtained by applying a public method on @var{ts},
%! or a dynSeries object built by extracting a variable from @var{ts}, or a dynSeries object containing a subsample of the all the variable in @var{ts}.
%! @end table
%! @sp 2
%! @strong{Example 1.} Let @var{ts} be a dynSeries object containing three variables named 'A1', 'A2' and 'A3'. Then the following syntax:
%! @example
%!   us = ts.A1;
%! @end example
%!will create a new dynSeries object @var{us} containing the variable 'A1'.
%! @sp 1
%! @strong{Example 2.} Let @var{ts} be a dynSeries object. Then the following syntax:
%! @example
%!   us = ts.log;
%! @end example
%!will create a new dynSeries object @var{us} containing all the variables of @var{ts} transformed by the neperian logarithm.
%! @sp 1
%! @strong{Example 3.} Let @var{ts} be a dynSeries object. The following syntax:
%! @example
%!   us = ts(3:50);
%! @end example
%!will create a new dynSeries object @var{us} by selecting a subsample out of @var{ts}.
%! @end deftypefn
%@eod:

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% Copyright (C) 2011, 2012 Dynare Team
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%
% 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/>.

% AUTHOR(S) stephane DOT adjemian AT univ DASH lemans DOT fr

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if length(S)==1 && isequal(S.type,'.')
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    switch S.subs
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      case {'data','nobs','vobs','name','tex','freq','time','init'}        % Public members.
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        us = builtin('subsref', ts, S);
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      case {'log','exp','ygrowth','qgrowth','ydiff','qdiff'}               % Give "dot access" to public methods.
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        us = feval(S.subs,ts);
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      case {'save'}
        us = NaN;
        save(ts);
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      otherwise                                                            % Extract a sub-object by selecting one variable.
        ndx = strmatch(S.subs,ts.name);
        if ~isempty(ndx)
            us = dynSeries();
            us.data = ts.data(:,ndx);
            us.name = deblank(ts.name(ndx,:));
            us.tex  = deblank(ts.tex(ndx,:));
            us.nobs = ts.nobs;
            us.vobs = 1;
            us.freq = ts.freq;
            us.init = ts.init;
            return
        else
            error('dynSeries::subsref: Unknown public method, public member or variable!')
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        end
    end
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    return
end
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if length(S)==1 && isequal(S.type,'()')
    if ischar(S.subs{1})
        us = dynSeries(S.subs{1});
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    elseif isa(S.subs{1},'dynDates')
        [junk,tdx] = intersect(ts.time.time,S.subs{1}.time,'rows');
        us = dynSeries();
        us.data = ts.data(tdx,:);
        us.name = deblank(ts.name);
        us.tex  = deblank(ts.tex);
        us.nobs = length(tdx);
        us.vobs = ts.vobs;
        us.freq = ts.freq;
        us.init = ts.init+tdx(1);
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    else
        % Extract a sub-object by selecting a sub-sample.
        if size(ts.data,2)>1
            S.subs = [S.subs, ':'];
        end
        us.data = builtin('subsref', ts.data, S);
        us.nobs = size(us.data,1);
        us.vobs = ts.vobs;
        us.freq = ts.freq;
        us.time = builtin('subsref', ts.time, S);
        us.init = ts.init+S.subs{1}(1);
        us.name = ts.name;
        us.tex  = ts.tex;
        return
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    end
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end
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if (length(S)==2) && (isequal(S(1).subs,'init'))
    if isequal(S(2).type,'.') && ( isequal(S(2).subs,'freq') || isequal(S(2).subs,'time') )
        us = builtin('subsref', ts.init, S(2));
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    else
        error('dynSeries:subsref:: I don''t understand what you are trying to do!')
    end
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    return
end

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if (length(S)==2) && (isequal(S(1).type,'.')) && (isequal(S(1).subs,'data')) && (isequal(S(2).type,'()')) 
    us = builtin('subsref',ts.data,S(2));
    return
end

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if (length(S)==1) && isequal(S(1).type,'{}')
    us = extract(ts,S(1).subs{:});
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    return
end

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if (length(S)==2) && isequal(S(1).type,'{}')
    us = extract(ts,S(1).subs{:});
    us = subsref(us, S(2));
    return
end


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if (length(S)==2) && isequal(S(1).subs,'save') && isequal(S(1).type,'.') && isequal(S(2).type,'()')
    us = NaN;
    save(ts,S(2).subs{:});
    return
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end

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if (length(S)==2) && isequal(S(1).subs,'set_names') && isequal(S(1).type,'.') && isequal(S(2).type,'()')
    us = set_names(ts,S(2).subs{:});
    return
end

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if (length(S)==2) && isequal(S(1).subs,'name') && isequal(S(1).type,'.') && isequal(S(2).type,'{}')
    us = ts.name{S(2).subs{1}};
    return
end

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%@test:1
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1(2:9);
%$
%$ % Expected results.
%$ e.data = [transpose(2:9),2*transpose(2:9)];
%$ e.nobs = 8;
%$ e.vobs = 2;
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%$ e.name = {'A1';'A2'};
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%$ e.freq = 1;
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%$ e.init = dynDate(2);
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%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
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%$ t(2) = dyn_assert(a.nobs,e.nobs);
%$ t(3) = dyn_assert(a.vobs,e.vobs);
%$ t(4) = dyn_assert(a.freq,e.freq);
%$ t(5) = dyn_assert(a.init,e.init);
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%$ T = all(t);
%@eof:1

%@test:2
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1.A1;
%$
%$ % Expected results.
%$ e.data = transpose(1:10);
%$ e.nobs = 10;
%$ e.vobs = 1;
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%$ e.name = {'A1'};
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%$ e.freq = 1;
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%$ e.init = dynDate(1);
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%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
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%$ t(2) = dyn_assert(a.init,e.init);
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%$ t(3) = dyn_assert(a.nobs,e.nobs);
%$ t(4) = dyn_assert(a.vobs,e.vobs);
%$ t(5) = dyn_assert(a.freq,e.freq);
%$ T = all(t);
%@eof:2

%@test:3
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1.log;
%$
%$ % Expected results.
%$ e.data = log(A);
%$ e.nobs = 10;
%$ e.vobs = 2;
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%$ e.name = {'A1';'A2'};
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%$ e.freq = 1;
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%$ e.init = dynDate(1);
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%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
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%$ t(2) = dyn_assert(a.nobs,e.nobs);
%$ t(3) = dyn_assert(a.vobs,e.vobs);
%$ t(4) = dyn_assert(a.freq,e.freq);
%$ t(5) = dyn_assert(a.init,e.init);
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%$ T = all(t);
%@eof:3
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%@test:4
%$ % Create an empty dynSeries object.
%$ dataset = dynSeries();
%$
%$ t = zeros(5,1);
%$
%$ try
%$    A = dataset('dynseries_test_data.csv');
%$    t(1) = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ % Check the results.
%$ if length(t)>1
%$     t(2) = dyn_assert(A.nobs,4);
%$     t(3) = dyn_assert(A.vobs,4);
%$     t(4) = dyn_assert(A.freq,4);
%$     t(5) = dyn_assert(A.init,dynDate('1990Q1'));
%$ end
%$ T = all(t);
%@eof:4
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%@test:5
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10),3*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2';'B1'};
%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1{'A1','B1'};
%$
%$ % Expected results.
%$ e.data = A(:,[1,3]);
%$ e.nobs = 10;
%$ e.vobs = 2;
%$ e.name = {'A1';'B1'};
%$ e.freq = 1;
%$ e.init = dynDate(1);
%$
%$ t(1) = dyn_assert(e.data,a.data);
%$ t(2) = dyn_assert(e.nobs,a.nobs);
%$ t(3) = dyn_assert(e.vobs,a.vobs);
%$ t(4) = dyn_assert(e.name,a.name);
%$ t(5) = dyn_assert(e.init,a.init);
%$ T = all(t);
%@eof:5

%@test:6
%$ % Define a data set.
%$ A = rand(10,24);
%$
%$ % Define names
%$ A_name = {'GDP_1';'GDP_2';'GDP_3'; 'GDP_4'; 'GDP_5'; 'GDP_6'; 'GDP_7'; 'GDP_8'; 'GDP_9'; 'GDP_10'; 'GDP_11'; 'GDP_12'; 'HICP_1';'HICP_2';'HICP_3'; 'HICP_4'; 'HICP_5'; 'HICP_6'; 'HICP_7'; 'HICP_8'; 'HICP_9'; 'HICP_10'; 'HICP_11'; 'HICP_12';};
%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1{'GDP_@0-9@'};
%$ b = ts1{'@A-Z@_1'};
%$
%$ % Expected results.
%$ e1.data = A(:,1:12);
%$ e1.nobs = 10;
%$ e1.vobs = 12;
%$ e1.name = {'GDP_1';'GDP_2';'GDP_3'; 'GDP_4'; 'GDP_5'; 'GDP_6'; 'GDP_7'; 'GDP_8'; 'GDP_9'; 'GDP_10'; 'GDP_11'; 'GDP_12'};
%$ e1.freq = 1;
%$ e1.init = dynDate(1);
%$ e2.data = A(:,[1, 13]);
%$ e2.nobs = 10;
%$ e2.vobs = 2;
%$ e2.name = {'GDP_1';'HICP_1'};
%$ e2.freq = 1;
%$ e2.init = dynDate(1);
%$
%$ % Check results.
%$ t(1) = dyn_assert(e1.data,a.data);
%$ t(2) = dyn_assert(e1.nobs,a.nobs);
%$ t(3) = dyn_assert(e1.vobs,a.vobs);
%$ t(4) = dyn_assert(e1.name,a.name);
%$ t(5) = dyn_assert(e1.init,a.init);
%$ t(6) = dyn_assert(e2.data,b.data);
%$ t(7) = dyn_assert(e2.nobs,b.nobs);
%$ t(8) = dyn_assert(e2.vobs,b.vobs);
%$ t(9) = dyn_assert(e2.name,b.name);
%$ t(10) = dyn_assert(e2.init,b.init);
%$ T = all(t);
%@eof:6

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%@test:7
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$ % Instantiate a time series object.
%$ try
%$    ts1 = dynSeries(A,[],A_name,[]);
%$    ts1.save;
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ T = all(t);
%@eof:7

%@test:8
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$ % Instantiate a time series object.
%$ try
%$    ts1 = dynSeries(A,[],A_name,[]);
%$    ts1.save('test_generated_data_file','m');
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
%$ T = all(t);
%@eof:8
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%@test:9
%$ % Define a data set.
%$ A = [transpose(1:60),2*transpose(1:60),3*transpose(1:60)];
%$
%$ % Define names
%$ A_name = {'A1';'A2';'B1'};
%$
%$ % Instantiate a time series object.
%$ ts1 = dynSeries(A,'1971Q1',A_name,[]);
%$
%$ % Define the range of a subsample.
%$ range = dynDate('1971Q2'):dynDate('1971Q4');
%$ % Call the tested method.
%$ a = ts1(range);
%$
%$ % Expected results.
%$ e.data = A(2:4,:);
%$ e.nobs = 3;
%$ e.vobs = 3;
%$ e.name = {'A1';'A2';'B1'};
%$ e.freq = 4;
%$ e.init = dynDate('1971Q2');
%$
%$ t(1) = dyn_assert(e.data,a.data);
%$ t(2) = dyn_assert(e.nobs,a.nobs);
%$ t(3) = dyn_assert(e.vobs,a.vobs);
%$ t(4) = dyn_assert(e.name,a.name);
%$ t(5) = dyn_assert(e.init,a.init);
%$ T = all(t);
%@eof:9