ENH _hdbscan HIERARCHY data type introduction
#25826
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thomasjpfan
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Mar 16, 2023
Co-authored-by: Julien Jerphanion <[email protected]>
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@thomasjpfan @jjerphan wondering what you two think of the PR now |
Co-authored-by: Julien Jerphanion <[email protected]>
Co-authored-by: Julien Jerphanion <[email protected]>
thomasjpfan
reviewed
Mar 28, 2023
| cluster = cluster_map[cluster_num] | ||
| max_lambda = deaths[cluster] | ||
| if max_lambda == 0.0 or not np.isfinite(lambda_array[n]): | ||
| if max_lambda == 0.0 or isinf(lambda_array[n]): |
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Should this be?
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| if max_lambda == 0.0 or isinf(lambda_array[n]): | |
| if max_lambda == 0.0 or not isinf(lambda_array[n]): |
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The original checks that it is not finite rather than not infinite, so I think the current isinf is correct -- unless I have it further mixed up somehow?
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Ah I'm thinking about:
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| if max_lambda == 0.0 or isinf(lambda_array[n]): | |
| if max_lambda == 0.0 or not isfinite(lambda_array[n]): |
Because of nan behavior:
not isfinite(NaN) == 1
isinf(NaN) == 0Is lambda_array[n] never nan by construction?
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Right, lambda_array stems from the computed minimum reachability distance, which is never expected to be nan since we separate those points before processing
thomasjpfan
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Mar 28, 2023
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May 16, 2023
Co-authored-by: Julien Jerphanion <[email protected]>
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Reference Issues/PRs
Towards #24686
What does this implement/fix? Explain your changes.
HIERARCHYdtypeandc-typefloat64_tarrays withHIERARCHYwhere appropriateAny other comments?
This is a blocker for more sweeping algorithm refactors and simplifications which rely on the structure of the dtype