[Octave-bug-tracker] [bug #65186] potential regression due to "isargout" changes

[Dmitri A. Sergatskov]

URL:
  <https://savannah.gnu.org/bugs/?65186>

                 Summary: potential regression due to "isargout" changes 
                   Group: GNU Octave
               Submitter: dasergatskov
               Submitted: Sat 20 Jan 2024 08:55:37 PM UTC
                Category: Interpreter
                Severity: 3 - Normal
                Priority: 5 - Normal
              Item Group: Regression
                  Status: None
             Assigned to: None
         Originator Name: 
        Originator Email: 
             Open/Closed: Open
                 Release: 9.0.90
         Discussion Lock: Any
        Operating System: GNU/Linux
           Fixed Release: None
         Planned Release: None


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Follow-up Comments:


-------------------------------------------------------
Date: Sat 20 Jan 2024 08:55:37 PM UTC By: Dmitri A. Sergatskov <dasergatskov>
With

changeset:   32783:56995fce2adc
branch:      stable
parent:      32780:e96e2f9f9f37
user:        John W. Eaton <jwe@octave.org>
date:        Fri Jan 19 14:06:27 2024 -0500
summary:     prepare for eventual removal of isargout

I see:

octave:1> pkg load statistics 
octave:2> test gpfit verbose
>>>>>
/home/dima/.local/share/octave/api-v58/packages/statistics-1.6.1/dist_fit/gpfit.m
***** demo
 ## Sample 2 populations from different generalized Pareto distibutions
 ## Assume location parameter is known
 mu = 0;
 rand ("seed", 5);    # for reproducibility
 r1 = gprnd (1, 2, mu, 20000, 1);
 rand ("seed", 2);    # for reproducibility
 r2 = gprnd (3, 1, mu, 20000, 1);
 r = [r1, r2];

 ## Plot them normalized and fix their colors
 hist (r, [0.1:0.2:100], 5);
 h = findobj (gca, "Type", "patch");
 set (h(1), "facecolor", "r");
 set (h(2), "facecolor", "c");
 ylim ([0, 1]);
 xlim ([0, 5]);
 hold on

 ## Estimate their α and β parameters
 k_sigmaA = gpfit (r(:,1));
 k_sigmaB = gpfit (r(:,2));

 ## Plot their estimated PDFs
 x = [0.01, 0.1:0.2:18];
 y = gppdf (x, k_sigmaA(1), k_sigmaA(2), mu);
 plot (x, y, "-pc");
 y = gppdf (x, k_sigmaB(1), k_sigmaB(2), mu);
 plot (x, y, "-sr");
 hold off
 legend ({"Normalized HIST of sample 1 with k=1 and σ=2", ...
          "Normalized HIST of sample 2 with k=2 and σ=2", ...
          sprintf("PDF for sample 1 with estimated k=%0.2f and σ=%0.2f", ...
                  k_sigmaA(1), k_sigmaA(2)), ...
          sprintf("PDF for sample 3 with estimated k=%0.2f and σ=%0.2f", ...
                  k_sigmaB(1), k_sigmaB(2))})
 title ("Three population samples from different generalized Pareto
distibutions")
 text (2, 0.7, "Known location parameter μ = 0")
 hold off
!!!!! demo failed
'data' undefined near line 232, column 24
octave:3> version -hgid
ans = 56995fce2adc


With previous changeset (32780:e96e2f9f9f37)

octave:1> pkg load statistics 
octave:2> test gpfit verbose
>>>>>
/home/dima/.local/share/octave/api-v58/packages/statistics-1.6.1/dist_fit/gpfit.m
***** demo
 ## Sample 2 populations from different generalized Pareto distibutions
 ## Assume location parameter is known
 mu = 0;
 rand ("seed", 5);    # for reproducibility
 r1 = gprnd (1, 2, mu, 20000, 1);
 rand ("seed", 2);    # for reproducibility
 r2 = gprnd (3, 1, mu, 20000, 1);
 r = [r1, r2];

 ## Plot them normalized and fix their colors
 hist (r, [0.1:0.2:100], 5);
 h = findobj (gca, "Type", "patch");
 set (h(1), "facecolor", "r");
 set (h(2), "facecolor", "c");
 ylim ([0, 1]);
 xlim ([0, 5]);
 hold on

 ## Estimate their α and β parameters
 k_sigmaA = gpfit (r(:,1));
 k_sigmaB = gpfit (r(:,2));

 ## Plot their estimated PDFs
 x = [0.01, 0.1:0.2:18];
 y = gppdf (x, k_sigmaA(1), k_sigmaA(2), mu);
 plot (x, y, "-pc");
 y = gppdf (x, k_sigmaB(1), k_sigmaB(2), mu);
 plot (x, y, "-sr");
 hold off
 legend ({"Normalized HIST of sample 1 with k=1 and σ=2", ...
          "Normalized HIST of sample 2 with k=2 and σ=2", ...
          sprintf("PDF for sample 1 with estimated k=%0.2f and σ=%0.2f", ...
                  k_sigmaA(1), k_sigmaA(2)), ...
          sprintf("PDF for sample 3 with estimated k=%0.2f and σ=%0.2f", ...
                  k_sigmaB(1), k_sigmaB(2))})
 title ("Three population samples from different generalized Pareto
distibutions")
 text (2, 0.7, "Known location parameter μ = 0")
 hold off
Press <enter> to continue: 
***** test
 shape = 5; scale = 2;
 x = gprnd (shape, scale, 0, 1, 100000);
 [hat, ci] = gpfit (x);
 assert (hat, [shape, scale], 1e-1);
 assert (ci, [shape, scale; shape, scale], 2e-1);
***** test
 shape = 1; scale = 1;
 x = gprnd (shape, scale, 0, 1, 100000);
 [hat, ci] = gpfit (x);
 assert (hat, [shape, scale], 1e-1);
 assert (ci, [shape, scale; shape, scale], 1e-1);
***** test
 shape = 3; scale = 2;
 x = gprnd (shape, scale, 0, 1, 100000);
 [hat, ci] = gpfit (x);
 assert (hat, [shape, scale], 1e-1);
 assert (ci, [shape, scale; shape, scale], 1e-1);
***** error<gpfit: X must be a vector.> gpfit (ones (2))
***** error<gpfit: X must contain only positive values.> gpfit ([-1, 2])
***** error<gpfit: X must contain only positive values.> gpfit ([0, 1, 2])
***** error<gpfit: wrong value for alpha.> gpfit ([1, 2], 0)
***** error<gpfit: wrong value for alpha.> gpfit ([1, 2], 1.2)
***** error<gpfit: OPTIONS must be a structure for 'fminsearch' function.>
...
 gpfit ([1:10], 0.05, 5)
PASSES 9 out of 9 tests
octave:3> test gpfit
PASSES 9 out of 9 tests
octave:4> version -hgid
ans = e96e2f9f9f37


statistics 1.6.1 

Dmitri.
-- 










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