From 24af83a10e31daf8e12b24292747a186e5305e44 Mon Sep 17 00:00:00 2001 From: Phil Schaf Date: Fri, 20 Dec 2024 17:19:58 +0100 Subject: [PATCH] Doc fixes for 1.11 --- docs/release-notes/1.11.0.md | 8 ++++---- src/scanpy/preprocessing/_simple.py | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/release-notes/1.11.0.md b/docs/release-notes/1.11.0.md index c7258ea271..a41103e0ec 100644 --- a/docs/release-notes/1.11.0.md +++ b/docs/release-notes/1.11.0.md @@ -6,14 +6,14 @@ - {func}`~scanpy.pp.sample` supports both upsampling and downsampling of observations and variables. {func}`~scanpy.pp.subsample` is now deprecated. {smaller}`G Eraslan & P Angerer` ({pr}`943`) - Add `layer` argument to {func}`scanpy.tl.score_genes` and {func}`scanpy.tl.score_genes_cell_cycle` {smaller}`L Zappia` ({pr}`2921`) - Prevent `raw` conflict with `layer` in {func}`~scanpy.tl.score_genes` {smaller}`S Dicks` ({pr}`3155`) -- Add support for `median` as an aggregation function to the `Aggregation` class in `scanpy.get._aggregated.py`. This allows for median-based aggregation of data (e.g., pseudobulk), complementing existing methods like mean- and sum-based aggregation {smaller}`M Dehkordi (Farhad)` ({pr}`3180`) +- Add support for `median` as an aggregation function to {func}`~scanpy.get.aggregate`. This allows for median-based aggregation of data (e.g., pseudobulk), complementing existing methods like mean- and sum-based aggregation {smaller}`M Dehkordi (Farhad)` ({pr}`3180`) - Add `key_added` argument to {func}`~scanpy.pp.pca`, {func}`~scanpy.tl.tsne` and {func}`~scanpy.tl.umap` {smaller}`P Angerer` ({pr}`3184`) - Support running {func}`scanpy.pp.pca` on sparse Dask arrays with the `'covariance_eigh'` solver {smaller}`P Angerer` ({pr}`3263`) -- Use upstreamed {class}`~sklearn.decomposition.PCA` implementation for {class}`~scipy.sparse.csr_array` and {class}`~scipy.sparse.csr_matrix` (see {ref}`sklearn:changes_1_4`) {smaller}`P Angerer` ({pr}`3267`) +- Use upstreamed {class}`~sklearn.decomposition.PCA` implementation for {class}`~scipy.sparse.csr_array` and {class}`~scipy.sparse.csr_matrix` (see scikit-learn {ref}`sklearn:changes_1_4`) {smaller}`P Angerer` ({pr}`3267`) - Add explicit support to {func}`scanpy.pp.pca` for `svd_solver='covariance_eigh'` {smaller}`P Angerer` ({pr}`3296`) -- Add support {class}`dask.array.Array` to {func}`scanpy.pp.calculate_qc_metrics` {smaller}`I Gold` ({pr}`3307`) +- Add support for {class}`dask.array.Array` to {func}`scanpy.pp.calculate_qc_metrics` {smaller}`I Gold` ({pr}`3307`) - Support `layer` parameter in {func}`scanpy.pl.highest_expr_genes` {smaller}`P Angerer` ({pr}`3324`) -- Run numba functions single-threaded when called from inside of a ThreadPool {smaller}`P Angerer` ({pr}`3335`) +- Run numba functions single-threaded when called from inside of a {class}`~multiprocessing.pool.ThreadPool` {smaller}`P Angerer` ({pr}`3335`) - Switch {func}`~scanpy.logging.print_header` and {func}`~scanpy.logging.print_versions` to {mod}`session_info2` {smaller}`P Angerer` ({pr}`3384`) - Add sampling probabilities/mask parameter `p` to {func}`~scanpy.pp.sample` {smaller}`P Angerer` ({pr}`3410`) diff --git a/src/scanpy/preprocessing/_simple.py b/src/scanpy/preprocessing/_simple.py index 821615676a..ac68edd376 100644 --- a/src/scanpy/preprocessing/_simple.py +++ b/src/scanpy/preprocessing/_simple.py @@ -885,7 +885,7 @@ def sample( Rows correspond to cells and columns to genes. fraction Sample to this `fraction` of the number of observations or variables. - (All of them, even if there are `0`s/`False`s in `p`.) + (All of them, even if there are `0`\\ s/`False`\\ s in `p`.) This can be larger than 1.0, if `replace=True`. See `axis` and `replace`. n