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Score normalizations

Merged Tiago de Freitas Pereira requested to merge score-normalizations into dask-pipelines
1 unresolved thread

This is a long MR with the following features:

  • Proper checkpointing of scores (BioAlgCheckpointWrapper). Still in pickle, though
  • Moved the score-writer outside of the VanillaBiometricsPipeline
  • Simplified the scoring by BioAlgorithm. Also made once SampleSet, dump one score.
  • Implemented a new pipeline that does Z, T and ZT score normalizations. Also created wrappers for Checkpointing and Dask this pipeline. Such pipeline has to wrap a VanillaBiometricsPipeline to work.
  • Adapted the CLI command, bob pipelines vanilla-biometrics to work with ZNorm. Now, if you want to ztnorm a pipeline, just do bob pipelines vanilla-biometrics --ztnorm

Don't know if someone is willing to review this one.

Edited by Tiago de Freitas Pereira

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  • 278 # Axi1 1=TNORM
    279 if axis == 1:
    280 return np.sqrt(
    281 np.sum(
    282 (
    283 norm_base_scores
    284 - np.tile(
    285 mu.reshape(norm_base_scores.shape[0], 1),
    286 (1, norm_base_scores.shape[1]),
    287 )
    288 )
    289 ** 2,
    290 axis=1,
    291 )
    292 / (norm_base_scores.shape[1] - 1)
    293 )
  • Tiago, I'll let someone with more experience in ztnorm review this.

  • Well, this person is myself LOL

    Basically this dumps the same output as bob.learn.em, but it works distributed :-)

  • We could finally close this one

    Closes #76 (closed)

  • added 1 commit

    • a626b376 - Chaged the post-processing mechanism

    Compare with previous version

  • added 2 commits

    • d9f5534b - Polishing ZT-Norm
    • 0414d3be - Polishing score serialization. It's impossible to do it in HDF5

    Compare with previous version

  • mentioned in commit b72b8022

  • mentioned in issue #105 (closed)

  • mentioned in issue #76 (closed)

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