Add cross_cov_matrix to transition data#13416
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Locally the test passes. |
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This adds a new update event AnalysisMatrixEvent, which sends the correlation matrix in the callback as a part of the event. Is is saved to posterior / transition storage section together with serialized event. Add AnalysisStorageEvent and sparse flag Rename posterior_id to ensemble_id Add artifacts endpoint This returns all the AnalysisStorageEvents as a list Add update endpoint Save matrix after threshold being applied Replace transition with blob Rebase with main Fixup for corr matrix to bytes conv Make progress_callback a partial function to provide ensemble automatyically Fixups for posterior ensemble Fixup test
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jonathan-eq
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May 22, 2026
jonathan-eq
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May 22, 2026
jonathan-eq
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May 22, 2026
jonathan-eq
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jonathan-eq
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| buf = io.BytesIO() | ||
| np.save(buf, corr_XY_matrix) |
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Do we have to do this manually, or can we use numpy.array.tobytes() directly?
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The difference is the tobytes just stores the data itself while np.save saves also the header, which might be a thing we want.
jonathan-eq
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May 22, 2026
xjules
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May 27, 2026
| sp.sparse.save_npz(blob_path, sparse_blob) | ||
| else: | ||
| blob_path = blob_dir / f"{stem}.npy" | ||
| np.save(blob_path, blob) |
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this should be bytes.
xjules
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May 27, 2026
| userdata: Mapping[str, Any] = {} | ||
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| class BlobOut(BaseModel): |
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Replace with the actual BlobStorageData | BlobStorageMatrix and init with validate_python
xjules
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May 27, 2026
| uri: str | ||
| file_size: int | ||
| ensemble_id: str | ||
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update_algorithm: ...
xjules
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May 27, 2026
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| class MatrixStorageData(BlobStorageData): | ||
| sparse: bool = False |
xjules
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May 27, 2026
| @@ -15,3 +16,8 @@ class BlobStorageData(BaseModel): | |||
| uri: str | |||
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{uuid}.blob <- bytes
xjules
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May 27, 2026
| @@ -15,3 +16,8 @@ class BlobStorageData(BaseModel): | |||
| uri: str | |||
| file_size: int | |||
| ensemble_id: str | |||
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file_type: "parquet", "numpy"
dafeda
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May 28, 2026
| data_type = str(matrix.dtype) | ||
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| sparsity = 1.0 - (np.count_nonzero(matrix) / matrix.size) | ||
| sparse = bool(sparsity > 0.5) |
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Is there a good reason for 0.5?
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Issue
Resolves #13296
Relates to #13378
Approach
This introduces:
AnalysisMatrixEvent- for sending the matrix to update_run_model.AnalysisStorageEvent- for storing the eventUpdate: I might need to re-think this a bit due to fact when loading the data back how the endpoint should look like.
(Screenshot of new behavior in GUI if applicable)
git rebase -i main --exec 'just rapid-tests')When applicable