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Merged
hyanwong merged 1 commit into from
Jan 7, 2026
Merged

remaining edits from #3359 #3361

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6 changes: 3 additions & 3 deletions python/tskit/trees.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9304,17 +9304,17 @@ def pca(
randomized singular value decomposition (rSVD) algorithm.

Concretely, take :math:`M` as the matrix of non-span-normalised
branch-based genetic relatedness values, for instance obtained by
genetic relatedness values, for instance obtained by
setting :math:`M_{ij}` to be the :meth:`~.TreeSequence.genetic_relatedness`
between sample :math:`i` and sample :math:`j` with ``mode="branch"``,
between sample :math:`i` and sample :math:`j` with the specified ``mode``,
``proportion=False`` and ``span_normalise=False``. Then by default this
returns the top ``num_components`` eigenvectors of :math:`M`, so that
``output.factors[i,k]`` is the position of sample `i` on the `k` th PC.
If ``samples`` or ``individuals`` are provided, then this does the same
thing, except with :math:`M_{ij}` either the relatedness between
``samples[i]`` and ``samples[j]`` or the average relatedness between the
nodes of ``individuals[i]`` and ``individuals[j]``, respectively.
Factors are normalized to have L2 norm 1, i.e.,
Factors are normalized to have norm 1, i.e.,
``output.factors[:,k] ** 2).sum() == 1)`` for any ``k``.

The parameters ``centre`` and ``mode`` are passed to
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