feature ndim

[mtar]

Description

Add method ndim to dndarray for NumPy-API-compatibility. Will replaces numdims()

Issue/s resolved: None

Changes proposed:

• additional DNDarray method ndim
• deprecation warning on numdims
• replace function calls

Type of change

New feature

Due Diligence

• All split configurations tested
• Multiple dtypes tested in relevant functions
• Documentation updated (if needed)
• Updated changelog.md under the title "Pending Additions"

Does this change modify the behaviour of other functions? If so, which?

no

[codecov]

Codecov Report

Merging #577 into master will increase coverage by 0.00%.
The diff coverage is 98.27%.

@@           Coverage Diff           @@
##           master     #577   +/-   ##
=======================================
  Coverage   96.47%   96.47%           
=======================================
  Files          75       75           
  Lines       15161    15169    +8     
=======================================
+ Hits        14626    14634    +8     
  Misses        535      535           

Impacted Files	Coverage Δ
heat/core/operations.py	92.77% <ø> (ø)
heat/regression/lasso.py	91.52% <75.00%> (ø)
heat/core/dndarray.py	96.84% <100.00%> (+0.01%)	⬆️
heat/core/indexing.py	100.00% <100.00%> (ø)
heat/core/linalg/basics.py	93.67% <100.00%> (ø)
heat/core/linalg/solver.py	68.36% <100.00%> (ø)
heat/core/manipulations.py	99.51% <100.00%> (ø)
heat/core/statistics.py	97.82% <100.00%> (ø)
heat/core/tests/test_dndarray.py	99.37% <100.00%> (+<0.01%)	⬆️
heat/core/tiling.py	96.35% <100.00%> (ø)
... and 1 more

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[ClaudiaComito]

YES! 👏
I'd be for not going through numdims though. In fact, I'd be for deprecating numdims and removing it before v1.0. What do you think?

[mtar]

I think so, too. Neither Numpy nor Pytorch use 'numdims'. ndim should be the preferred method name.
Does Numpy have any aliases for this function?

Pytorch's equivalent function is called dim(). ndim() and ndimension() are two aliases I'm aware of. Should we add them? I don't think that we need those as we're striving for numpy API compatibility.