Missing tests: is_block_positive

[purva-thakre]

Description

Related to some uncovered lines in #241

Last line is still not covered by this PR.

Todos

Notable points that this PR has either accomplished or will accomplish.

• TODO 1

Questions

• Question1

Status

• Ready to go

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (2226c46) 97.2% compared to head (4940957) 97.4%.
Report is 3 commits behind head on master.

Additional details and impacted files

@@           Coverage Diff            @@
##           master    #335     +/-   ##
========================================
+ Coverage    97.2%   97.4%   +0.1%     
========================================
  Files         152     152             
  Lines        3046    3044      -2     
  Branches      726     725      -1     
========================================
+ Hits         2961    2965      +4     
+ Misses         50      48      -2     
+ Partials       35      31      -4     

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[purva-thakre]

@vprusso Do you mind explaining the use-case scenario for these lines? I am struggling with defining the input matrix and dims for this case.

toqito/toqito/matrix_props/is_block_positive.py

Lines 71 to 75 in 2226c46

	dim = np.array([dim, dim_xy / dim]) # pylint: disable=redefined-variable-type
	if np.abs(dim[1] - np.round(dim[1])) >= 2 * dim_xy * np.finfo(float).eps:
	raise ValueError(
	"If `dim` is a scalar, it must evenly divide the length of the matrix."
	)

[purva-thakre]

To do: Search for open ended discussions in published refs for below.

toqito/toqito/matrix_props/is_block_positive.py

Lines 109 to 111 in 2226c46

	return RuntimeError(
	"Unable to determine k-block positivity. Please consider increasing the relative tolerance or the effort level."
	)

[vprusso]

@vprusso Do you mind explaining the use-case scenario for these lines? I am struggling with defining the input matrix and dims for this case.

toqito/toqito/matrix_props/is_block_positive.py

Lines 71 to 75 in 2226c46

	dim = np.array([dim, dim_xy / dim]) # pylint: disable=redefined-variable-type
	if np.abs(dim[1] - np.round(dim[1])) >= 2 * dim_xy * np.finfo(float).eps:
	raise ValueError(
	"If `dim` is a scalar, it must evenly divide the length of the matrix."
	)

All I can really say is that I believe this was an artifact of the way in which the same type of thing was checked in the QETLAB implementation. I'm not sure I have a more satisfying impression of this at the moment. There was a similar check in the realignment.py code as well, as I ended up removing it as I wasn't able to even construct a test case that would hit this block.

Not sure if that's overly zealous or if perhaps there's a reason why this makes sense to do in MATLAB vs. Python. So we could either remove it, or, keep it for now and expect that it will remain uncovered.

[purva-thakre]

marking this ready for review even though the line below is uncovered.

toqito/toqito/matrix_props/is_block_positive.py

Lines 109 to 111 in 2226c46

	return RuntimeError(
	"Unable to determine k-block positivity. Please consider increasing the relative tolerance or the effort level."
	)

[vprusso]

🚀