[Octave-patch-tracker] [patch #10103] Add weighted standard deviation feature to 'std'

[Nicholas Jankowski]

Follow-up Comment #14, patch #10103 (project octave):

Ok, I'm noticing a number of test failures.

before making a patch, always run 'test <function>' to be sure there aren't
any surprises.

a few seem to be %!error tests in std that just needed variable names or error
message text updated now that var is generating the messages:


Expected <OPT must be 0 or 1>, but got <var: W must be 0 or 1 or a vector of
positive integers>

Expected <DIM must be an integer>, but got <var: DIM must be a positive
integer scalar, vector, or 'all'>


Easy enough to fix. but more importantly, both var and std have issues with
empty array handling:

While you force var([]) and std([]) to return NaN like matlab using an
'isempty', this fails the following test in std:


>> test std
***** assert (std (ones (1,3,0,2)), ones (1,3,0,2))
!!!!! test failed
ASSERT errors for:  assert (std (ones (1, 3, 0, 2)),ones (1, 3, 0, 2))

  Location  |  Observed  |  Expected  |  Reason
     .          O(1x1)     E(1x3x0x2)    Dimensions don't match


Empty arrays can have dimensionality, and that can matter if we want to
maintain mathematical consistency:
https://octave.org/doc/latest/Empty-Matrices.html

it turns out that the test above is actually incorrect in matlab, and it
should be:

assert (std (ones (1,3,0,2)), ones (1,1,0,2))


Maybe that was a matlab change as they not too long ago tried to bring
consistency to their NaN and empty array handling throughout all of their
functions. if dim=1 you get ones(1,3,0,2), but if dim=2, you don't.

There should be, but isn't a corresponding test in var.


So, noting that the same empty array can be created with NaN(1,0). i think in
the past rather than just check isempty I did something like:

i did something like

if isempty(x)
  outsize = size(x);
  outsize(dim)=1;
  retval = NaN(outsize);
else
...


Now, that's not quite enough of course.  because in matlab the empty array
processing seems to crash into the 2D vector handling algorithm.  see all the
following:

Matlab 2021a:

>> var([])
ans =
   NaN
>> var([],[],1)
ans =
  1×0 empty double row vector
>> var([],[],2)
ans =
  0×1 empty double column vector
>> var([],[],3)
ans =
     []
>> std(ones(0,0))
ans =
   NaN
>> std(ones(1,0))
ans =
   NaN
>> std(ones(0,1))
ans =
   NaN
>> std(ones(1,0),[],1)
ans =
  1×0 empty double row vector
>> std(ones(1,0),[],2)
ans =
   NaN
>> std(ones(0,1),[],1)
ans =
   NaN
>> std(ones(0,1),[],2)
ans =
  0×1 empty double column vector



and adding in the nd array handling:

>> std(ones(1,3,0,2),[],1)
ans =
  1×3×0×2 empty double array
>> std(ones(1,3,0,2),[],2)
ans =
  1×1×0×2 empty double array
>> std(ones(1,3,0,2),[],3)
ans(:,:,1,1) =
   NaN   NaN   NaN
ans(:,:,1,2) =
   NaN   NaN   NaN
>> std(ones(1,3,0,2),[],4)
ans =
  1×3×0 empty double array


there's quite a few things to try to capture. again, let me look at how I
handled something similar before and i'll see if it can just drop in here.



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