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Fix docs
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stes committed Jul 12, 2023
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10 changes: 6 additions & 4 deletions cebra/integrations/sklearn/metrics.py
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Expand Up @@ -163,8 +163,9 @@ def _consistency_datasets(
labels: List of labels corresponding to each embedding and to use for alignment
between them.
num_discretization_bins: Number of values for the digitalized common labels. The discretized labels are used
for embedding alignment. Also see the ``n_bins`` argument in :py:mod:`~..helpers.align_embeddings`
for more information on how this parameter is used internally. This argument is only used if ``labels``
for embedding alignment. Also see the ``n_bins`` argument in
:py:mod:`cebra.integrations.sklearn.helpers.align_embeddings` for more information on how this
parameter is used internally. This argument is only used if ``labels``
is not ``None`` and the given labels are continuous and not already discrete.
Returns:
Expand Down Expand Up @@ -327,8 +328,9 @@ def consistency_score(
trained on the **same dataset**. *Consistency between datasets* means the consistency between embeddings
obtained from models trained on **different datasets**, such as different animals, sessions, etc.
num_discretization_bins: Number of values for the digitalized common labels. The discretized labels are used
for embedding alignment. Also see the ``n_bins`` argument in :py:mod:`~..helpers.align_embeddings`
for more information on how this parameter is used internally. This argument is only used if ``labels``
for embedding alignment. Also see the ``n_bins`` argument in
:py:mod:`cebra.integrations.sklearn.helpers.align_embeddings` for more information on how this
parameter is used internally. This argument is only used if ``labels``
is not ``None``, alignment between datasets is used (``between = "datasets"``), and the given labels
are continuous and not already discrete.
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