Faster Adjoint/Transpose-UniformScaling arithmetic

[jishnub]

Avoids hitting slow generic methods.
Discussed in https://discourse.julialang.org/t/very-long-time-for-addition-of-complex-identity-matrix-to-transposed-sparse-matrix/129465.
After this, the following are comparable:

julia> A = sprandn(90, 90, 0.01);

julia> @btime ($A + complex(0,1.) * I);
  1.313 μs (13 allocations: 8.02 KiB)

julia> @btime (transpose($A) + complex(0,1.) * I);
  1.416 μs (13 allocations: 8.02 KiB)

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 93.75%. Comparing base (c4a477f) to head (d4201d6).
Report is 4 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #1366      +/-   ##
==========================================
- Coverage   93.75%   93.75%   -0.01%     
==========================================
  Files          34       34              
  Lines       15724    15732       +8     
==========================================
+ Hits        14742    14749       +7     
- Misses        982      983       +1     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[stevengj]

LGTM. Is there any concern over changing the type of the result of A' + I?

[jishnub]

I don't think this is much of a concern. The return types aren't guaranteed across releases, and one often needs to refine these for performance.