diff --git a/docs/release-notes/0.3.0.md b/docs/release-notes/0.3.0.md index 7b3f48cc44..285e6248d1 100644 --- a/docs/release-notes/0.3.0.md +++ b/docs/release-notes/0.3.0.md @@ -1,7 +1,7 @@ (v0.3.0)= ### 0.3.0 {small}`2017-11-16` -- {class}`~anndata.AnnData` gains method {meth}`~anndata.AnnData.concatenate` {smaller}`A Wolf` +- {class}`~anndata.AnnData` gains method `AnnData.concatenate` {smaller}`A Wolf` - {class}`~anndata.AnnData` is available as the separate [anndata] package {smaller}`P Angerer, A Wolf` - results of [PAGA](https://github.com/theislab/paga) simplified {smaller}`A Wolf` diff --git a/src/scanpy/external/pp/_mnn_correct.py b/src/scanpy/external/pp/_mnn_correct.py index 1bef795ef0..83e499ca34 100644 --- a/src/scanpy/external/pp/_mnn_correct.py +++ b/src/scanpy/external/pp/_mnn_correct.py @@ -68,13 +68,13 @@ def mnn_correct( # noqa: PLR0913 correction. Typically, a list of highly variable genes (HVGs). When set to `None`, uses all vars. batch_key - The `batch_key` for :meth:`~anndata.AnnData.concatenate`. + The `batch_key` for ``anndata.AnnData.concatenate``. Only valid when `do_concatenate` and supplying `AnnData` objects. index_unique - The `index_unique` for :meth:`~anndata.AnnData.concatenate`. + The `index_unique` for ``anndata.AnnData.concatenate``. Only valid when `do_concatenate` and supplying `AnnData` objects. batch_categories - The `batch_categories` for :meth:`~anndata.AnnData.concatenate`. + The `batch_categories` for ``anndata.AnnData.concatenate``. Only valid when `do_concatenate` and supplying AnnData objects. k Number of mutual nearest neighbors. diff --git a/src/scanpy/external/tl/_harmony_timeseries.py b/src/scanpy/external/tl/_harmony_timeseries.py index 95f0565fad..e59fd3503d 100644 --- a/src/scanpy/external/tl/_harmony_timeseries.py +++ b/src/scanpy/external/tl/_harmony_timeseries.py @@ -83,7 +83,7 @@ def harmony_timeseries( >>> from itertools import product >>> import pandas as pd - >>> from anndata import AnnData + >>> from anndata import AnnData, concat >>> import scanpy as sc >>> import scanpy.external as sce @@ -97,11 +97,12 @@ def harmony_timeseries( >>> adata_ref = sc.datasets.pbmc3k() >>> start = [596, 615, 1682, 1663, 1409, 1432] - >>> adata = AnnData.concatenate( - ... *(adata_ref[i : i + 1000] for i in start), + >>> adata = concat( + ... [adata_ref[i : i + 1000] for i in start], ... join="outer", - ... batch_key="sample", - ... batch_categories=[f"sa{i}_Rep{j}" for i, j in product((1, 2, 3), (1, 2))], + ... label="sample", + ... keys=[f"sa{i}_Rep{j}" for i, j in product((1, 2, 3), (1, 2))], + ... index_unique="-", ... ) >>> time_points = adata.obs["sample"].str.split("_", expand=True)[0] >>> adata.obs["time_points"] = pd.Categorical( diff --git a/tests/external/test_harmony_timeseries.py b/tests/external/test_harmony_timeseries.py index 3c3155aec1..66e37795e4 100644 --- a/tests/external/test_harmony_timeseries.py +++ b/tests/external/test_harmony_timeseries.py @@ -2,7 +2,7 @@ from itertools import product -from anndata import AnnData +from anndata import concat import scanpy as sc import scanpy.external as sce @@ -15,11 +15,12 @@ def test_load_timepoints_from_anndata_list(): adata_ref = pbmc3k() start = [596, 615, 1682, 1663, 1409, 1432] - adata = AnnData.concatenate( - *(adata_ref[i : i + 1000] for i in start), + adata = concat( + [adata_ref[i : i + 1000] for i in start], join="outer", - batch_key="sample", - batch_categories=[f"sa{i}_Rep{j}" for i, j in product((1, 2, 3), (1, 2))], + label="sample", + keys=[f"sa{i}_Rep{j}" for i, j in product((1, 2, 3), (1, 2))], + index_unique="-", ) adata.obs["time_points"] = adata.obs["sample"].str.split("_", expand=True)[0] adata.obs["time_points"] = adata.obs["time_points"].astype("category")