subsref.m 11.8 KB
Newer Older
1
function B = subsref(A, S)
Stéphane Adjemian's avatar
Stéphane Adjemian committed
2
3
%@info:
%! @deftypefn {Function File} {@var{us} =} subsref (@var{ts},S)
Stéphane Adjemian's avatar
Stéphane Adjemian committed
4
%! @anchor{@dynSeries/subsref}
Stéphane Adjemian's avatar
Stéphane Adjemian committed
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
%! @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:

47
% Copyright (C) 2011, 2012, 2013 Dynare Team
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
%
% 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/>.

64
65
66
switch S(1).type
  case '.'
    switch S(1).subs
67
      case {'data','nobs','vobs','name','tex','freq','time','init'}        % Public members.
68
        B = builtin('subsref', A, S(1));
69
      case {'log','exp','ygrowth','qgrowth','ydiff','qdiff'}               % Give "dot access" to public methods.
70
71
        B = feval(S(1).subs,A);
      case {'save'}                                                        % Save dynSeries object on disk (default is a csv file). 
72
        B = NaN;
73
74
75
76
77
78
        if length(S)==2 && strcmp(S(2).type,'()')
            save(A,S(2).subs{:});
            S = shiftS(S);
        else
            save(A);
        end
79
80
81
82
83
84
85
86
      case {'size'}
        if length(S)==2 && strcmp(S(2).type,'()') && ~isempty(S(2).subs)
            B = size(A,S(2).subs{1});
            S = shiftS(S);
        else
            [x,y] = size(A);
            B = [x, y];
        end
87
88
89
      case {'rename','tex_rename'}
        B = feval(S(1).subs,A,S(2).subs{:});
        S = shiftS(S);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
90
      otherwise                                                            % Extract a sub-object by selecting one variable.
91
        ndx = strmatch(S(1).subs,A.name,'exact');
Stéphane Adjemian's avatar
Stéphane Adjemian committed
92
        if ~isempty(ndx)
93
94
            B = dynSeries();
            B.data = A.data(:,ndx);
95
96
            B.name = A.name(ndx);
            B.tex = A.tex(ndx);
97
98
99
100
101
102
            B.tex  = deblank(A.tex(ndx,:));
            B.nobs = A.nobs;
            B.vobs = 1;
            B.freq = A.freq;
            B.init = A.init;
            B.time = A.time;
Stéphane Adjemian's avatar
Stéphane Adjemian committed
103
104
        else
            error('dynSeries::subsref: Unknown public method, public member or variable!')
105
        end
106
107
108
109
110
111
112
113
114
115
116
117
118
119
    end    
  case '()'
    if ischar(S(1).subs{1})
        % If ts is an empty dynSeries object, populate this object by reading data in a file.
        if isempty(A)
            B = dynSeries(S(1).subs{1});
        else
            error(['dynSeries::subsref: dynSeries object ''' inputname(1) '''  is not empty!'])
        end
    elseif isa(S(1).subs{1},'dynDates')
        % Extract a subsample using a dynDates object
        [junk,tdx] = intersect(A.time.time,S(1).subs{1}.time,'rows');
        B = dynSeries();
        B.data = A.data(tdx,:);
120
121
        B.name = A.name;
        B.tex  = A.tex;
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
        B.nobs = length(tdx);
        B.vobs = A.vobs;
        B.freq = A.freq;
        B.init = A.init+tdx(1);
        B.time = A.time(tdx,:);
    elseif isvector(S(1).subs{1}) && all(isint(S(1).subs{1}))
        % Extract a subsample using a vector of integers (observation index).
        if all(S(1).subs{1}>0) && all(S(1).subs{1}<=A.nobs)
            if size(A.data,2)>1
                S(1).subs = [S(1).subs, ':'];
            end
            B.data = builtin('subsref', A.data, S(1));
            B.nobs = size(B.data,1);
            B.vobs = A.vobs;
            B.freq = A.freq;
            B.time = builtin('subsref', A.time, S(1));
            B.init = A.init+S(1).subs{1}(1);
            B.name = A.name;
            B.tex  = A.tex;
        else
            error('dynSeries::subsref: Indices are out of bounds!')
143
        end
144
    else
145
        error('dynSeries::subsref: I have no idea of what you are trying to do!')
146
    end
147
148
149
150
  case '{}'
    B = extract(A,S(1).subs{:});
  otherwise
    error('dynSeries::subsref: What the Hell are you doin'' here?!')
151
152
end

153
154
155
S = shiftS(S);
if ~isempty(S)
    B = subsref(B, S);
156
157
end

158
159
160
161
162
%@test:1
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
163
%$ A_name = {'A1';'A2'};
164
165
166
167
168
169
170
171
172
173
174
%$
%$ % 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;
175
%$ e.name = {'A1';'A2'};
176
%$ e.freq = 1;
177
%$ e.init = dynDate(2);
178
179
180
%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
181
182
183
184
%$ 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);
185
186
187
188
189
190
191
192
%$ T = all(t);
%@eof:1

%@test:2
%$ % Define a data set.
%$ A = [transpose(1:10),2*transpose(1:10)];
%$
%$ % Define names
193
%$ A_name = {'A1';'A2'};
194
195
196
197
198
199
200
201
202
203
204
%$
%$ % 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;
205
%$ e.name = {'A1'};
206
%$ e.freq = 1;
207
%$ e.init = dynDate(1);
208
209
210
%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
211
%$ t(2) = dyn_assert(a.init,e.init);
212
213
214
215
216
217
218
219
220
221
222
%$ 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
223
%$ A_name = {'A1';'A2'};
224
225
226
227
228
229
230
231
232
233
234
%$
%$ % 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;
235
%$ e.name = {'A1';'A2'};
236
%$ e.freq = 1;
237
%$ e.init = dynDate(1);
238
239
240
%$
%$ % Check the results.
%$ t(1) = dyn_assert(a.data,e.data);
241
242
243
244
%$ 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);
245
246
%$ T = all(t);
%@eof:3
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269

%@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
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341

%@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

342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
%@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
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409

%@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
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432

%@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 = dynSeries(A,'1971Q1',A_name,[]);
%$
%$ % Test the size method.
%$ B = ts1.size();
%$ C = ts1.size(1);
%$ D = ts1.size(2);
%$ E = ts1.size;
%$
%$ t(1) = dyn_assert(B,[60, 3]);
%$ t(2) = dyn_assert(E,[60, 3]);
%$ t(3) = dyn_assert(C,60);
%$ t(4) = dyn_assert(D,3);
%$ T = all(t);
%@eof:10