function B = subsref(A, S) % --*-- Unitary tests --*--
%@info:
%! @deftypefn {Function File} {@var{us} =} subsref (@var{ts},S)
%! @anchor{@dseries/subsref}
%! @sp 1
%! Overloads the subsref method for the Dynare time series class (@ref{dseries}).
%! @sp 2
%! @strong{Inputs}
%! @sp 1
%! @table @ @var
%! @item ts
%! Dynare time series object instantiated by @ref{dseries}.
%! @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 dseries object built by extracting a variable from @var{ts}, or a dseries object containing a subsample of the all the variable in @var{ts}.
%! @end table
%! @sp 2
%! @strong{Example 1.} Let @var{ts} be a dseries object containing three variables named 'A1', 'A2' and 'A3'. Then the following syntax:
%! @example
%! us = ts.A1;
%! @end example
%!will create a new dseries object @var{us} containing the variable 'A1'.
%! @sp 1
%! @strong{Example 2.} Let @var{ts} be a dseries object. Then the following syntax:
%! @example
%! us = ts.log;
%! @end example
%!will create a new dseries 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 dseries object. The following syntax:
%! @example
%! us = ts(3:50);
%! @end example
%!will create a new dseries object @var{us} by selecting a subsample out of @var{ts}.
%! @end deftypefn
%@eod:
% Copyright (C) 2011-2017 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 .
switch S(1).type
case '.'
switch S(1).subs
case {'data','name','tex','dates','ops', 'tags'} % Public members.
if length(S)>1 && isequal(S(2).type,'()') && isempty(S(2).subs)
error(['dseries::subsref: ' S(1).subs ' is not a method but a member!'])
end
B = builtin('subsref', A, S(1));
case 'nobs'
% Returns the number of observations.
B = rows(A.data);
case 'vobs'
% Returns the number of variables.
B = columns(A.data);
case 'init'
% Returns a dates object (first date).
B = A.dates(1);
case 'last'
% Returns a dates object (last date).
B = A.dates(end);
case 'freq'
% Returns an integer characterizing the data frequency (1, 4, 12 or 52)
B = A.dates.freq;
case 'length'
error(['dseries::subsref: we do not support the length operator on ' ...
'dseries. Please use ''nobs'' or ''vobs''']);
case 'save'
% Save dseries object on disk (default is a mat file).
B = NaN;
if isequal(length(S),2)
if strcmp(S(2).type,'()')
if isempty(S(2).subs)
save(A);
else
if isempty(S(2).subs{1})
save(A,'',S(2).subs{2});
else
save(A,S(2).subs{:});
end
end
S = shiftS(S,1);
else
error('dseries::subsref: Wrong syntax.')
end
elseif isequal(length(S),1)
save(A);
else
error('dseries::subsref: Call to save method must come in last position!')
end
case 'struct'
B = dseries2struct(A);
case {'baxter_king_filter', 'baxter_king_filter_', ...
'cumsum','cumsum_', ...
'insert', ...
'pop','pop_', ...
'cumprod','cumprod_', ...
'remove','remove_', ...
'onesidedhptrend','onesidedhptrend_', ...
'onesidedhpcycle','onesidedhpcycle_', ...
'lag','lag_', ...
'lead','lead_', ...
'hptrend','hptrend_', ...
'hpcycle','hpcycle_', ...
'chain','chain_', ...
'detrend','detrend_', ...
'exist', ...
'mean', ...
'std', ...
'center','center_', ...
'log','log_', ...
'exp','exp_', ...
'ygrowth','ygrowth_', ...
'qgrowth','qgrowth_', ...
'mgrowth','mgrowth_', ...
'ydiff','ydiff_', ...
'qdiff','qdiff_', ...
'diff', 'diff_', ...
'mdiff','mdiff_', ...
'abs','abs_', ...
'isnan', ...
'firstdate', ...
'firstobservedperiod', ...
'lastobservedperiod', ...
'lineartrend', ...
'resetops', 'resettags'}
if length(S)>1 && isequal(S(2).type,'()')
if isempty(S(2).subs)
B = feval(S(1).subs,A);
S = shiftS(S,1);
else
B = feval(S(1).subs,A,S(2).subs{:});
S = shiftS(S,1);
end
else
B = feval(S(1).subs,A);
end
case 'size'
if isequal(length(S),2) && strcmp(S(2).type,'()')
if isempty(S(2).subs)
[x,y] = size(A);
B = [x, y];
else
B = size(A,S(2).subs{1});
end
S = shiftS(S,1);
elseif isequal(length(S),1)
[x,y] = size(A);
B = [x, y];
else
error('dseries::subsref: Call to size method must come in last position!')
end
case {'set_names','rename','rename_','tex_rename','tex_rename_', 'tag'}
B = feval(S(1).subs,A,S(2).subs{:});
S = shiftS(S,1);
case {'disp'}
feval(S(1).subs,A);
return
otherwise % Extract a sub-object by selecting one variable.
ndx = find(strcmp(S(1).subs,A.name));
if ~isempty(ndx)
B = dseries();
B.data = A.data(:,ndx);
B.name = A.name(ndx);
B.tex = A.tex(ndx);
B.dates = A.dates;
B.ops = A.ops(ndx);
tagnames = fieldnames(A.tags);
for i=1:length(tagnames)
B.tags.(tagnames{i}) = A.tags.(tagnames{i})(ndx);
end
else
error('dseries::subsref: Unknown public method, public member or variable!')
end
end
case '()'
if ischar(S(1).subs{1}) && ~isdate(S(1).subs{1})
% If ts is an empty dseries object, populate this object by reading data in a file.
if isempty(A)
B = dseries(S(1).subs{1});
else
error('dseries::subsref: dseries object is not empty!')
end
elseif isscalar(S(1).subs{1}) && isnumeric(S(1).subs{1}) && isint(S(1).subs{1})
% Input is also interpreted as a backward/forward operator
if S(1).subs{1}>0
B = feval('lead', A, S(1).subs{1});
elseif S(1).subs{1}<0
B = feval('lag', A, -S(1).subs{1});
else
% Do nothing.
B = A;
end
elseif isdates(S(1).subs{1}) || isdate(S(1).subs{1})
if isdate(S(1).subs{1})
Dates = dates(S(1).subs{1});
else
Dates = S(1).subs{1};
end
% Test if Dates is out of bounds
if min(Dates)max(A.dates)
error(['dseries::subsref: Indices are out of bounds! Subsample cannot end after ' date2string(A.dates(end)) '.'])
end
% Extract a subsample using a dates object
[junk,tdx] = intersect(A.dates.time,Dates.time,'rows');
B = copy(A);
B.data = B.data(tdx,:);
B.dates = B.dates(tdx);
elseif isvector(S(1).subs{1}) && all(isint(S(1).subs{1}))
error('dseries::subsref: It is not possible to select observations with a vector of integers. You have to index with a dates object instead!');
else
error('dseries::subsref: I have no idea of what you are trying to do!')
end
case '{}'
if iscellofchar(S(1).subs)
B = extract(A,S(1).subs{:});
elseif isequal(length(S(1).subs),1) && all(isint(S(1).subs{1}))
idx = S(1).subs{1};
if max(idx)>size(A.data,2) || min(idx)<1
error('dseries::subsref: Indices are out of bounds!')
end
B = dseries();
B.data = A.data(:,idx);
B.name = A.name(idx);
B.tex = A.tex(idx);
B.dates = A.dates;
B.ops = A.ops(idx);
tagnames = fieldnames(A.tags);
for i=1:length(tagnames)
B.tags.(tagnames{i}) = A.tags.(tagnames{i})(idx);
end
else
error('dseries::subsref: What the Hell are you tryin'' to do?!')
end
otherwise
error('dseries::subsref: What the Hell are you doin'' here?!')
end
S = shiftS(S,1);
if ~isempty(S)
B = subsref(B, S);
end
%@test:1
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$ % Instantiate a time series object.
%$ ts1 = dseries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1(ts1.dates(2:9));
%$
%$ % Expected results.
%$ e.data = [transpose(2:9),2*transpose(2:9)];
%$ e.nobs = 8;
%$ e.vobs = 2;
%$ e.name = {'A1';'A2'};
%$ e.freq = 1;
%$ e.init = dates(1,2);
%$
%$ % Check the results.
%$ t(1) = dassert(a.data,e.data);
%$ t(2) = dassert(a.nobs,e.nobs);
%$ t(3) = dassert(a.vobs,e.vobs);
%$ t(4) = dassert(a.freq,e.freq);
%$ t(5) = dassert(a.init,e.init);
%$ T = all(t);
%@eof:1
%@test:2
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$ % Instantiate a time series object.
%$ ts1 = dseries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1.A1;
%$
%$ % Expected results.
%$ e.data = transpose(1:10);
%$ e.nobs = 10;
%$ e.vobs = 1;
%$ e.name = {'A1'};
%$ e.freq = 1;
%$ e.init = dates(1,1);
%$
%$ % Check the results.
%$ t(1) = dassert(a.data,e.data);
%$ t(2) = dassert(a.init,e.init);
%$ t(3) = dassert(a.nobs,e.nobs);
%$ t(4) = dassert(a.vobs,e.vobs);
%$ t(5) = dassert(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
%$ A_name = {'A1';'A2'};
%$
%$ % Instantiate a time series object.
%$ ts1 = dseries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ a = ts1.log;
%$
%$ % Expected results.
%$ e.data = log(A);
%$ e.nobs = 10;
%$ e.vobs = 2;
%$ e.name = {'A1';'A2'};
%$ e.freq = 1;
%$ e.init = dates(1,1);
%$
%$ % Check the results.
%$ t(1) = dassert(a.data,e.data);
%$ t(2) = dassert(a.nobs,e.nobs);
%$ t(3) = dassert(a.vobs,e.vobs);
%$ t(4) = dassert(a.freq,e.freq);
%$ t(5) = dassert(a.init,e.init);
%$ T = all(t);
%@eof:3
%@test:4
%$ % Create an empty dseries object.
%$ dataset = dseries();
%$
%$ t = zeros(5,1);
%$
%$ try
%$ [strfile, status] = urlwrite('http://www.dynare.org/Datasets/dseries/dynseries_test_data.csv','dynseries_test_data.csv');
%$ if ~status
%$ error()
%$ end
%$ A = dseries('dynseries_test_data.csv');
%$ delete('dynseries_test_data.csv');
%$ t(1) = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ % Check the results.
%$ if length(t)>1
%$ t(2) = dassert(A.nobs,4);
%$ t(3) = dassert(A.vobs,4);
%$ t(4) = dassert(A.freq,4);
%$ t(5) = dassert(A.init,dates('1990Q1'));
%$ end
%$ T = all(t);
%@eof:4
%@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 = dseries(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 = dates(1,1);
%$
%$ t(1) = dassert(e.data,a.data);
%$ t(2) = dassert(e.nobs,a.nobs);
%$ t(3) = dassert(e.vobs,a.vobs);
%$ t(4) = dassert(e.name,a.name);
%$ t(5) = dassert(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 = dseries(A,[],A_name,[]);
%$
%$ % Call the tested method.
%$ try
%$ a = ts1{'[GDP_[0-9]]'};
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$ try
%$ b = ts1{'[[A-Z]*_1]'};
%$ t(2) = 1;
%$ catch
%$ t(2) = 0;
%$ end
%$ try
%$ warning off all
%$ c = ts1{'[A-Z]_1'};
%$ warning on all
%$ t(3) = 0;
%$ catch
%$ t(3) = 1;
%$ end
%$
%$ % Expected results.
%$ e1.data = A(:,1:9);
%$ e1.nobs = 10;
%$ e1.vobs = 9;
%$ e1.name = {'GDP_1';'GDP_2';'GDP_3'; 'GDP_4'; 'GDP_5'; 'GDP_6'; 'GDP_7'; 'GDP_8'; 'GDP_9'};
%$ e1.freq = 1;
%$ e1.init = dates(1,1);
%$ e2.data = A(:,[1 13]);
%$ e2.nobs = 10;
%$ e2.vobs = 2;
%$ e2.name = {'GDP_1';'HICP_1'};
%$ e2.freq = 1;
%$ e2.init = dates(1,1);
%$
%$ % Check results.
%$ t(4) = dassert(e1.data,a.data);
%$ t(5) = dassert(e1.nobs,a.nobs);
%$ t(6) = dassert(e1.vobs,a.vobs);
%$ t(7) = dassert(e1.name,a.name);
%$ t(8) = dassert(e1.init,a.init);
%$ t(9) = dassert(e2.data,b.data);
%$ t(10) = dassert(e2.nobs,b.nobs);
%$ t(11) = dassert(e2.vobs,b.vobs);
%$ t(12) = dassert(e2.name,b.name);
%$ t(13) = dassert(e2.init,b.init);
%$ T = all(t);
%@eof:6
%@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 = dseries(A,[],A_name,[]);
%$ ts1.save('ts1');
%$ t = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ delete('ts1.mat');
%$
%$ 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 = dseries(A,[],A_name,[]);
%$ ts1.save('test_generated_data_file','m');
%$ delete('test_generated_data_file.m');
%$ t = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ T = all(t);
%@eof:8
%@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 = dseries(A,'1971Q1',A_name,[]);
%$
%$ % Define the range of a subsample.
%$ range = dates('1971Q2'):dates('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 = dates('1971Q2');
%$
%$ t(1) = dassert(e.data,a.data);
%$ t(2) = dassert(e.nobs,a.nobs);
%$ t(3) = dassert(e.vobs,a.vobs);
%$ t(4) = dassert(e.name,a.name);
%$ t(5) = dassert(e.init,a.init);
%$ T = all(t);
%@eof:9
%@test:10
%$ % 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 = dseries(A,'1971Q1',A_name,[]);
%$
%$ % Test the size method.
%$ B = ts1.size();
%$ C = ts1.size(1);
%$ D = ts1.size(2);
%$ E = ts1.size;
%$
%$ t(1) = dassert(B,[60, 3]);
%$ t(2) = dassert(E,[60, 3]);
%$ t(3) = dassert(C,60);
%$ t(4) = dassert(D,3);
%$ T = all(t);
%@eof:10
%@test:11
%$ % 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 = dseries(A,'1971Q1',A_name,[]);
%$
%$ % Test the size method.
%$ B = ts1{1};
%$ C = ts1{[1,3]};
%$ D = ts1{'A1'};
%$
%$ t(1) = dassert(B.name{1},'A1');
%$ t(2) = dassert(B.data,A(:,1));
%$ t(3) = dassert(C.name{1},'A1');
%$ t(4) = dassert(C.data(:,1),A(:,1));
%$ t(5) = dassert(C.name{2},'B1');
%$ t(6) = dassert(C.data(:,2),A(:,3));
%$ t(7) = dassert(D.name{1},'A1');
%$ t(8) = dassert(D.data,A(:,1));
%$ T = all(t);
%@eof:11
%@test:12
%$ % 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 = dseries(A,[],A_name,[]);
%$ ts1.save();
%$ t = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ delete('dynare_series.mat')
%$
%$ T = all(t);
%@eof:12
%@test:13
%$ try
%$ data = transpose(0:1:50);
%$ ts = dseries(data,'1950Q1');
%$ a = ts.lag;
%$ b = ts.lead;
%$ c = ts(-1);
%$ d = ts(1);
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$
%$ if t(1)>1
%$ t(2) = (a==c);
%$ t(3) = (b==d);
%$ end
%$
%$ T = all(t);
%@eof:13
%@test:14
%$ try
%$ ds = dseries(transpose(1:5));
%$ ts = ds(ds.dates(2:3));
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$
%$ if t(1)>1
%$ t(2) = isdseries(ts);
%$ t(3) = isequal(ts.data,ds.data(2:3));
%$ end
%$
%$ T = all(t);
%@eof:14
%@test:15
%$ try
%$ ds = dseries(transpose(1:5));
%$ ts = ds(ds.dates(2:6));
%$ t(1) = 0;
%$ catch
%$ t(1) = 1;
%$ end
%$
%$ T = all(t);
%@eof:15
%@test:16
%$ try
%$ ds = dseries(transpose(1:5));
%$ ts = ds(dates('1Y'):dates('6Y'));
%$ t(1) = 0;
%$ catch
%$ t(1) = 1;
%$ end
%$
%$ T = all(t);
%@eof:16
%@test:17
%$ try
%$ ds = dseries(transpose(1:5));
%$ ts = ds(dates('-2Y'):dates('4Y'));
%$ t(1) = 0;
%$ catch
%$ t(1) = 1;
%$ end
%$
%$ T = all(t);
%@eof:17