subsref.m 18.4 KB
Newer Older
1
2
3
4
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
47
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:

Houtan Bastani's avatar
Houtan Bastani committed
48
% Copyright (C) 2011-2016 Dynare Team
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
%
% 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/>.

switch S(1).type
  case '.'
    switch S(1).subs
      case {'data','name','tex','dates'}        % 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));
73
      case {'log','log_','exp','exp_','ygrowth','qgrowth','ydiff','qdiff','abs','isnan','firstdate','firstobservedperiod'}  % Give "dot access" to public methods without args.
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
        B = feval(S(1).subs,A);
        if length(S)>1 && isequal(S(2).type,'()') && isempty(S(2).subs)
            S = shiftS(S,1);
        end
      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;
93
      case {'lag','lead','hptrend','hpcycle','chain','detrend','exist','mean','std','center'} % Methods with less than two arguments.
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
        if length(S)>1 && isequal(S(2).type,'()')
            if isempty(S(2).subs)
                B = feval(S(1).subs,A);
                S = shiftS(S,1);
            else
                if ~ischar(S(2).subs{1}) && length(S(2).subs{1})>1
                    error(['dseries::subsref: ' S(1).subs{1} ' method admits no more than one argument!'])
                end
                B = feval(S(1).subs,A,S(2).subs{1});
                S = shiftS(S,1);
            end
        else
            B = feval(S(1).subs,A);
        end
      case {'cumsum','insert','pop','cumprod','remove'} % Methods with less than three argument.
        if length(S)>1 && isequal(S(2).type,'()')
            if isempty(S(2).subs)
                B = feval(S(1).subs,A);
                S = shiftS(S,1);
            else
                if length(S(2).subs)>2
                    error(['dseries::subsref: ' S(1).subs{1} ' method admits no more than two arguments!'])
                end
                B = feval(S(1).subs,A,S(2).subs{:});
                S = shiftS(S,1);
            end
        else
            B = feval(S(1).subs,A);
        end
      case 'baxter_king_filter'
        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{1})
                S = shiftS(S,1);
            end
        else
            B = feval(S(1).subs,A);
        end
      case 'save'                                                        % Save dseries object on disk (default is a csv file).
        B = NaN;
        if isequal(length(S),2)
            if strcmp(S(2).type,'()')
                if isempty(S(2).subs)
140
                    save(A);
141
142
                else
                    if isempty(S(2).subs{1})
143
                        save(A,'',S(2).subs{2});
144
145
146
147
148
149
150
151
152
                    else
                        save(A,S(2).subs{:});
                    end
                end
                S = shiftS(S,1);
            else
                error('dseries::subsref: Wrong syntax.')
            end
        elseif isequal(length(S),1)
153
            save(A);
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
        else
            error('dseries::subsref: Call to save method must come in last position!')
        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','tex_rename'}
        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;
        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
196
            error('dseries::subsref: dseries object is not empty!')
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
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
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
        end
    elseif isa(S(1).subs{1},'dynTimeIndex')
        % shift backward/forward (lag/lead) dseries object
        shift = S(1).subs{1}.index;
        if shift>0
            B = feval('lead',A,shift);
        elseif shift<0
            B = feval('lag',A,-shift);
        else
            % Do nothing.
            B = A;
        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)<min(A.dates)
            error(['dseries::subsref: Indices are out of bounds! Subsample cannot start before ' date2string(A.dates(1)) '.'])
        end
        if  max(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 = dseries();
        B.data = A.data(tdx,:);
        B.name = A.name;
        B.tex  = A.tex;
        B.dates = A.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;
    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
Stéphane Adjemian's avatar
Stéphane Adjemian committed
366
367
368
369
370
371
%$    [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');
372
373
374
375
376
377
378
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
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
%$    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.
%$ 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 = 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(1) = dassert(e1.data,a.data);
%$ t(2) = dassert(e1.nobs,a.nobs);
%$ t(3) = dassert(e1.vobs,a.vobs);
%$ t(4) = dassert(e1.name,a.name);
%$ t(5) = dassert(e1.init,a.init);
%$ t(6) = dassert(e2.data,b.data);
%$ t(7) = dassert(e2.nobs,b.nobs);
%$ t(8) = dassert(e2.vobs,b.vobs);
%$ t(9) = dassert(e2.name,b.name);
%$ t(10) = 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
%$
474
475
%$ delete('ts1.csv');
%$
476
477
478
479
480
481
482
483
484
485
486
487
488
489
%$ 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');
490
%$    delete('test_generated_data_file.m');
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
%$    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,[]);
589
%$    ts1.save();
590
591
592
593
594
%$    t = 1;
%$ catch
%$    t = 0;
%$ end
%$
595
%$ delete('dynare_series.csv')
596
%$
597
598
599
%$ T = all(t);
%@eof:12

Stéphane Adjemian's avatar
Stéphane Adjemian committed
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
% % @test:13
% %$ try
% %$     data = transpose(0:1:50);
% %$     ts = dseries(data,'1950Q1');
% %$     a = ts.lag;
% %$     b = ts.lead;
% %$     tt = dynTimeIndex();
% %$     c = ts(tt-1);
% %$     d = ts(tt+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
621

Stéphane Adjemian's avatar
Stéphane Adjemian committed
622
%@test:13 %14
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
%$ 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);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
641
%@eof:13
642

Stéphane Adjemian's avatar
Stéphane Adjemian committed
643
%@test:14 %15
644
645
646
647
648
649
650
651
652
653
654
655
656
657
%$ 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);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
658
%@eof:14
659

Stéphane Adjemian's avatar
Stéphane Adjemian committed
660
%@test:15 %16
661
662
663
664
665
666
667
668
669
%$ try
%$     ds = dseries(transpose(1:5));
%$     ts = ds(ds.dates(2:6));
%$     t(1) = 0;
%$ catch
%$     t(1) = 1;
%$ end
%$
%$ T = all(t);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
670
%@eof:15
671

Stéphane Adjemian's avatar
Stéphane Adjemian committed
672
%@test:16 %17
673
674
675
676
677
678
679
680
681
%$ try
%$     ds = dseries(transpose(1:5));
%$     ts = ds(dates('1Y'):dates('6Y'));
%$     t(1) = 0;
%$ catch
%$     t(1) = 1;
%$ end
%$
%$ T = all(t);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
682
%@eof:16
683

Stéphane Adjemian's avatar
Stéphane Adjemian committed
684
%@test:17 %18
685
686
687
688
689
690
691
692
693
%$ try
%$     ds = dseries(transpose(1:5));
%$     ts = ds(dates('-2Y'):dates('4Y'));
%$     t(1) = 0;
%$ catch
%$     t(1) = 1;
%$ end
%$
%$ T = all(t);
Stéphane Adjemian's avatar
Stéphane Adjemian committed
694
%@eof:17