Implement fastpair

[Mec-iS]

extract what is working from #17:

• implement pairwise dissimiliarities
• implement fastpair (all test-cases pass)
• improve memory usage by avoid usage of connectivity matrix

These features can be used in the future to implement additive clustering or other novel features.

may be of interest for @danieljrmay

[codecov-commenter]

Codecov Report

Merging #142 (b650b4c) into development (d905ebe) will increase coverage by 0.32%.
The diff coverage is 94.85%.

@@               Coverage Diff               @@
##           development     #142      +/-   ##
===============================================
+ Coverage        83.39%   83.71%   +0.32%     
===============================================
  Files               78       80       +2     
  Lines             8377     8591     +214     
===============================================
+ Hits              6986     7192     +206     
- Misses            1391     1399       +8     

Impacted Files	Coverage Δ
src/algorithm/neighbour/mod.rs	78.57% <ø> (ø)
src/algorithm/neighbour/distances.rs	66.66% <66.66%> (ø)
src/algorithm/neighbour/fastpair.rs	95.67% <95.67%> (ø)
src/svm/svc.rs	89.75% <0.00%> (+0.30%)	⬆️
src/error/mod.rs	56.00% <0.00%> (+8.00%)	⬆️

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[Mec-iS]

Implemented benchmark:

FastPair/fastpair --- n_samples: 100, n_features: 10                                                                            
                        time:   [406.55 us 410.09 us 414.64 us]
Found 7 outliers among 100 measurements (7.00%)
  6 (6.00%) high mild
  1 (1.00%) high severe
FastPair/brute --- n_samples: 100, n_features: 10                                                                             
                        time:   [1.1809 ms 1.1957 ms 1.2120 ms]
Found 6 outliers among 100 measurements (6.00%)
  5 (5.00%) high mild
  1 (1.00%) high severe
----------------------------------------------------------------------------
FastPair/fastpair --- n_samples: 100, n_features: 100                                                                             
                        time:   [2.1368 ms 2.1482 ms 2.1606 ms]
Found 3 outliers among 100 measurements (3.00%)
  3 (3.00%) high mild
FastPair/brute --- n_samples: 100, n_features: 100                                                                             
                        time:   [4.2466 ms 4.2732 ms 4.3008 ms]
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild
----------------------------------------------------------------------------
FastPair/fastpair --- n_samples: 100, n_features: 1000                                                                            
                        time:   [21.002 ms 21.129 ms 21.272 ms]
Found 8 outliers among 100 measurements (8.00%)
  5 (5.00%) high mild
  3 (3.00%) high severe
FastPair/brute --- n_samples: 100, n_features: 1000                                                                            
                        time:   [43.918 ms 44.168 ms 44.431 ms]
Found 4 outliers among 100 measurements (4.00%)
  4 (4.00%) high mild
----------------------------------------------------------------------------
Benchmarking FastPair/fastpair --- n_samples: 1000, n_features: 10:
FastPair/fastpair --- n_samples: 1000, n_features: 10                                                                            
                        time:   [58.740 ms 59.057 ms 59.409 ms]
Found 7 outliers among 100 measurements (7.00%)
  5 (5.00%) high mild
  2 (2.00%) high severe
Benchmarking FastPair/brute --- n_samples: 1000, n_features: 10:
FastPair/brute --- n_samples: 1000, n_features: 10                                                                            
                        time:   [117.68 ms 118.20 ms 118.85 ms]
Found 5 outliers among 100 measurements (5.00%)
  2 (2.00%) high mild
  3 (3.00%) high severe
----------------------------------------------------------------------------
Benchmarking FastPair/fastpair --- n_samples: 1000, n_features: 100:
FastPair/fastpair --- n_samples: 1000, n_features: 100                                                                            
                        time:   [221.43 ms 223.30 ms 225.28 ms]
Found 2 outliers among 100 measurements (2.00%)
  2 (2.00%) high mild
Benchmarking FastPair/brute --- n_samples: 1000, n_features: 100:
FastPair/brute --- n_samples: 1000, n_features: 100                                                                            
                        time:   [456.94 ms 460.50 ms 464.30 ms]
Found 7 outliers among 100 measurements (7.00%)
  5 (5.00%) high mild
  2 (2.00%) high severe
----------------------------------------------------------------------------
Benchmarking FastPair/fatpair --- n_samples: 1000, n_features:
FastPair/fastpair --- n_samples: 1000, n_features: 1000                                                                            
                        time:   [2.9984 s 3.0228 s 3.0484 s]
Found 2 outliers among 100 measurements (2.00%)
  2 (2.00%) high mild
Benchmarking FastPair/brute --- n_samples: 1000, n_features: 1000:
FastPair/brute --- n_samples: 1000, n_features: 1000                                                                            
                        time:   [5.9347 s 5.9732 s 6.0130 s]

[morenol]

LGTM, I added a couple of comments

[morenol]

LGTM, thanks!