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Adressing #220.

@LeonStadelmann LeonStadelmann requested a review from MUCDK May 21, 2025 14:08
for cond in conditions_adata & conditions_pred:
true_counts[name][cond] = self.validation_adata[name][
self.validation_adata[name].obs[self.condition_id_key] == cond
].X.toarray()
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@LeonStadelmann LeonStadelmann May 21, 2025

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Could we potentially go OOM here when using real data? I was not sure @MUCDK

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@MUCDK MUCDK May 22, 2025

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should be fine, because we first subset the adata before densifying.

two things here:

  1. provide the option to extract any adata.X or any adata.layers[key], similar how we e.g. do it in moscot
  2. bear in mind that adata.X can be both sparse and dense

@LeonStadelmann
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@MUCDK Your suggestions have been implemented, pinged since i cant request a review right now.

self._dataloader: TrainSampler | None = None
self._trainer: CellFlowTrainer | None = None
self._validation_data: dict[str, ValidationData] = {}
self._validation_adata: dict[str, ad.Anndata] = {}
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can we make these attributes of the callbacks directly?

self.layers = layers
self.log_prefix = log_prefix

def add_validation_adata(
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this can be part of __init__, can't it?

Comment on lines 109 to 111
for callback in callbacks:
if isinstance(callback, PCADecodedMetrics2):
callback.add_validation_adata(self.validation_adata)
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I don't think this would be needed if validation_adata was an attribute of the callback, would it?

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Let's try to make the validation_adata an attribute of the callback, as outlined in the comments.

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2 participants