Add additional matching modes to run_reconstruction (#333) #336
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| rows = _make_pairs_spatial(['a', 'b', 'c', 'd', 'e'],num_neighbors=2, locations=[(20,0,0),(10,0,0),(5,0,0),(2,0,0), (0,0,0)]) | ||
| expected = [['a', 'b', 'c'], | ||
| ['b', 'c', 'd'], | ||
| ['c', 'd', 'e'], | ||
| ['d', 'e']] | ||
| assert rows == expected |
Collaborator
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Bit confused here: focusing on b for example it looks like
- b gets matched with a due to
['a', 'b', 'c'] - b gets matched with c
- b gets matched with d due to
['b', 'c', 'd']
So b is getting matched with 3 neighbors, while num_neightbors is 2.
Is it a mistake or is there a subtlety to the interpretation of num_neighbors?
Author
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This is expected. b's two nearest neighbors are c and d. However b is also the nearest neighbor of a, so b will be matched with items a,c,d.
This lack of symmetry is better exemplified in the first test:
rows = _make_pairs_spatial(['a', 'b', 'c', 'd', 'e'],num_neighbors=1, locations=[(20,0,0),(10,0,0),(5,0,0),(2,0,0), (0,0,0)])
expected = [['a', 'b'],
['b', 'c'],
['c', 'd'],
['d', 'e']]
b is being matched with two items, a and c, even though num_neighbors=1.
Collaborator
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Ah, thank you I get it now
This adds support for 'sequential' and 'spatial' matching strategies, in addition to the existing 'exhaustive' and 'sequential_loop' modes. The matching mode must now be explicitly specified via the `matching_mode` argument instead of being inferred from `window_radius`. The 'spatial' mode requires 3D `locations` and uses nearest-neighbor matching.
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This adds support for 'sequential' and 'spatial' matching strategies, in addition to the existing 'exhaustive' and 'sequential_loop' modes.
The matching mode must now be explicitly specified via the
matching_modeargument instead of being inferred fromwindow_radius.The 'spatial' mode requires 3D
locationsand uses nearest-neighbor matching.