374 lines
9.9 KiB
Matlab
374 lines
9.9 KiB
Matlab
function us = subsref(ts, S)
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%@info:
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%! @deftypefn {Function File} {@var{us} =} subsref (@var{ts},S)
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%! @anchor{@dynSeries/subsref}
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%! @sp 1
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%! Overloads the subsref method for the Dynare time series class (@ref{dynSeries}).
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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 ts
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%! Dynare time series object instantiated by @ref{dynSeries}.
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%! @item S
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%! Matlab's structure array S with two fields, type and subs. The type field is string containing '()', '@{@}', or '.', where '()' specifies
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%! integer subscripts, '@{@}' specifies cell array subscripts, and '.' specifies subscripted structure fields. The subs field is a cell array
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%! or a string containing the actual subscripts (see matlab's documentation).
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%! @end table
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%! @sp 1
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%! @strong{Outputs}
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%! @sp 1
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%! @table @ @var
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%! @item us
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%! 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},
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%! 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}.
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%! @end table
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%! @sp 2
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%! @strong{Example 1.} Let @var{ts} be a dynSeries object containing three variables named 'A1', 'A2' and 'A3'. Then the following syntax:
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%! @example
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%! us = ts.A1;
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%! @end example
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%!will create a new dynSeries object @var{us} containing the variable 'A1'.
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%! @sp 1
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%! @strong{Example 2.} Let @var{ts} be a dynSeries object. Then the following syntax:
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%! @example
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%! us = ts.log;
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%! @end example
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%!will create a new dynSeries object @var{us} containing all the variables of @var{ts} transformed by the neperian logarithm.
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%! @sp 1
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%! @strong{Example 3.} Let @var{ts} be a dynSeries object. The following syntax:
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%! @example
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%! us = ts(3:50);
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%! @end example
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%!will create a new dynSeries object @var{us} by selecting a subsample out of @var{ts}.
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%! @end deftypefn
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%@eod:
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% Copyright (C) 2011, 2012 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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% 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'} % Give "dot access" to public methods.
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us = feval(S.subs,ts);
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case {'save'}
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us = NaN;
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save(ts);
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otherwise % Extract a sub-object by selecting one variable.
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ndx = strmatch(S.subs,ts.name);
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if ~isempty(ndx)
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us = dynSeries();
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us.data = ts.data(:,ndx);
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us.name = deblank(ts.name(ndx,:));
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us.tex = deblank(ts.tex(ndx,:));
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us.nobs = ts.nobs;
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us.vobs = 1;
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us.freq = ts.freq;
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us.init = ts.init;
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return
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else
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error('dynSeries::subsref: Unknown public method, public member or variable!')
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end
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end
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return
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end
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if length(S)==1 && isequal(S.type,'()')
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if ischar(S.subs{1})
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us = dynSeries(S.subs{1});
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else
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% Extract a sub-object by selecting a sub-sample.
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if size(ts.data,2)>1
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S.subs = [S.subs, ':'];
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end
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us.data = builtin('subsref', ts.data, S);
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us.nobs = size(us.data,1);
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us.vobs = ts.vobs;
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us.freq = ts.freq;
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us.time = builtin('subsref', ts.time, S);
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us.init = ts.init+S.subs{1}(1);
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us.name = ts.name;
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us.tex = ts.tex;
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return
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end
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end
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if (length(S)==2) && (isequal(S(1).subs,'init'))
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if isequal(S(2).type,'.') && ( isequal(S(2).subs,'freq') || isequal(S(2).subs,'time') )
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us = builtin('subsref', ts.init, S(2));
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else
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error('dynSeries:subsref:: I don''t understand what you are trying to do!')
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end
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return
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end
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if (length(S)==1) && isequal(S(1).type,'{}')
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us = extract(ts,S(1).subs{:});
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return
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end
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if (length(S)==2) && isequal(S(1).type,'{}')
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us = extract(ts,S(1).subs{:});
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us = subsref(us, S(2));
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return
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end
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if (length(S)==2) && isequal(S(1).subs,'save') && isequal(S(1).type,'.') && isequal(S(2).type,'()')
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us = NaN;
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save(ts,S(2).subs{:});
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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,'()')
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us = set_names(ts,S(2).subs{:});
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return
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end
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if (length(S)==2) && isequal(S(1).subs,'name') && isequal(S(1).type,'.') && isequal(S(2).type,'{}')
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us = ts.name{S(2).subs{1}};
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return
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end
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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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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$
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%$ % Instantiate a time series object.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$
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%$ % Call the tested method.
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%$ a = ts1(2:9);
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%$
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%$ % Expected results.
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%$ e.data = [transpose(2:9),2*transpose(2:9)];
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%$ e.nobs = 8;
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%$ 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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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(a.data,e.data);
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%$ t(2) = dyn_assert(a.nobs,e.nobs);
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%$ t(3) = dyn_assert(a.vobs,e.vobs);
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%$ t(4) = dyn_assert(a.freq,e.freq);
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%$ t(5) = dyn_assert(a.init,e.init);
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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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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$
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%$ % Instantiate a time series object.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$
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%$ % Call the tested method.
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%$ a = ts1.A1;
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%$
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%$ % Expected results.
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%$ e.data = transpose(1:10);
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%$ e.nobs = 10;
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%$ 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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%$
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%$ % Check the results.
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%$ 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);
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%$ t(4) = dyn_assert(a.vobs,e.vobs);
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%$ t(5) = dyn_assert(a.freq,e.freq);
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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(1:10),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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%$
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%$ % Instantiate a time series object.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$
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%$ % Call the tested method.
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%$ a = ts1.log;
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%$
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%$ % Expected results.
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%$ e.data = log(A);
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%$ e.nobs = 10;
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%$ 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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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(a.data,e.data);
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%$ t(2) = dyn_assert(a.nobs,e.nobs);
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%$ t(3) = dyn_assert(a.vobs,e.vobs);
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%$ t(4) = dyn_assert(a.freq,e.freq);
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%$ t(5) = dyn_assert(a.init,e.init);
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%$ T = all(t);
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%@eof:3
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%@test:4
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%$ % Create an empty dynSeries object.
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%$ dataset = dynSeries();
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%$
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%$ t = zeros(5,1);
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%$
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%$ try
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%$ A = dataset('dynseries_test_data.csv');
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%$ t(1) = 1;
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%$ catch
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%$ t = 0;
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%$ end
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%$
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%$ % Check the results.
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%$ if length(t)>1
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%$ t(2) = dyn_assert(A.nobs,4);
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%$ t(3) = dyn_assert(A.vobs,4);
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%$ t(4) = dyn_assert(A.freq,4);
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%$ t(5) = dyn_assert(A.init,dynDate('1990Q1'));
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%$ end
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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),3*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2';'B1'};
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%$
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%$ % Instantiate a time series object.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$
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%$ % Call the tested method.
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%$ a = ts1{'A1','B1'};
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%$
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%$ % Expected results.
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%$ e.data = A(:,[1,3]);
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%$ e.nobs = 10;
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%$ e.vobs = 2;
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%$ e.name = {'A1';'B1'};
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%$ e.freq = 1;
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%$ e.init = dynDate(1);
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%$
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%$ t(1) = dyn_assert(e.data,a.data);
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%$ t(2) = dyn_assert(e.nobs,a.nobs);
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%$ t(3) = dyn_assert(e.vobs,a.vobs);
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%$ t(4) = dyn_assert(e.name,a.name);
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%$ t(5) = dyn_assert(e.init,a.init);
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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 = rand(10,24);
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%$
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%$ % Define names
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%$ 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';};
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%$
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%$ % Instantiate a time series object.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$
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%$ % Call the tested method.
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%$ a = ts1{'GDP_@0-9@'};
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%$ b = ts1{'@A-Z@_1'};
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%$
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%$ % Expected results.
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%$ e1.data = A(:,1:12);
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%$ e1.nobs = 10;
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%$ e1.vobs = 12;
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%$ 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'};
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%$ e1.freq = 1;
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%$ e1.init = dynDate(1);
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%$ e2.data = A(:,[1, 13]);
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%$ e2.nobs = 10;
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%$ e2.vobs = 2;
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%$ e2.name = {'GDP_1';'HICP_1'};
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%$ e2.freq = 1;
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%$ e2.init = dynDate(1);
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%$
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%$ % Check results.
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%$ t(1) = dyn_assert(e1.data,a.data);
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%$ t(2) = dyn_assert(e1.nobs,a.nobs);
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%$ t(3) = dyn_assert(e1.vobs,a.vobs);
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%$ t(4) = dyn_assert(e1.name,a.name);
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%$ t(5) = dyn_assert(e1.init,a.init);
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%$ t(6) = dyn_assert(e2.data,b.data);
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%$ t(7) = dyn_assert(e2.nobs,b.nobs);
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%$ t(8) = dyn_assert(e2.vobs,b.vobs);
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%$ t(9) = dyn_assert(e2.name,b.name);
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%$ t(10) = dyn_assert(e2.init,b.init);
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%$ T = all(t);
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%@eof:6
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%@test:7
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%$ % Define a data set.
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%$ A = [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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%$
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%$ % Instantiate a time series object.
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%$ try
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts1.save;
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%$ t = 1;
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%$ catch
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%$ t = 0;
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%$ end
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%$
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%$ T = all(t);
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%@eof:7
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%@test:8
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%$ % Define a data set.
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%$ A = [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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%$
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%$ % Instantiate a time series object.
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%$ try
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts1.save('test_generated_data_file','m');
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%$ t = 1;
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%$ catch
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%$ t = 0;
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%$ end
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%$
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%$ T = all(t);
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%@eof:8
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