ENH: mean_interbuilding_distance and building_adjacency

[martinfleis]

Gosh I spent way too much time on this...

mean_interbuilding_distance:

35s new
57s old

Given my first attempt took 5mins, I call this a victory.

building_adjacency:

 old: 251 ms ± 14.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
 new: 422 ms ± 12.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

of which 330 ms is assign_self_weight which will be used in other functions so I'm wondering if it is worth adding a keyword self_weighted=True to skip this. In practice it is nearly negligible difference though...

These two functions also quite significantly change the API compared to the original. @jGaboardi can you give it a thought whether it makes sense in this way? I think it does and it is more flexible than before but it is different.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 97.6%. Comparing base (4037c70) to head (399cf39).
Report is 6 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##            main    #556     +/-   ##
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+ Coverage   97.4%   97.6%   +0.3%     
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  Files         26      30      +4     
  Lines       4328    4796    +468     
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+ Hits        4214    4682    +468     
  Misses       114     114             

Files	Coverage Δ
momepy/functional/_distribution.py	100.0% <100.0%> (ø)
momepy/functional/tests/test_distribution.py	100.0% <100.0%> (ø)
momepy/functional/tests/test_shape.py	100.0% <100.0%> (ø)

[jGaboardi]

These two functions also quite significantly change the API compared to the original. @jGaboardi can you give it a thought whether it makes sense in this way? I think it does and it is more flexible than before but it is different.

I think it makes sense, cleaner and more efficient for sure.

[martinfleis]

of which 330 ms is assign_self_weight which will be used in other functions so I'm wondering if it is worth adding a keyword self_weighted=True to skip this. In practice it is nearly negligible difference though...

Solved in 0d897cc by cheaply (10ms) checking if the graph already has self-weights and assigning only if they do not. Which means that if you pass self-weighted graph, the new implementation takes about half the time compared to the original.