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An algorithm for curating a graph of animal sightings

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WildMeOrg/wbia-tpl-lca

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LCA Algorithm Repository

Summary status as of 2020-06-18

Summary status as of 2019-09-14:

Tested on Python 3.7

Can run simulations using either ground truth clusters specified in a json file (see gt_ex.json) or using ground truth clusters generated from a gamma distribution. Parameters of the simulation can be set inside the main area of run_from_simulation.py

Example of running on a pre-specified ground-truth

python run_from_simulator.py gt_ex.json tmp

If you leave out the gt_ex.json it runs the gamma-distribution-generated ground-truth. This is a bit ugly and I will fix it soon.

Other than significant clean-up, here are major to dos:

  1. Add nodes and edges
  2. Delete nodes
  3. Use initial clustering with a name anchor so that the name stays with the node with the lowest id.
  4. Provide intermediate clustering results on demand.

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An algorithm for curating a graph of animal sightings

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