Shorten method descriptions (#842)

* shorten method descriptions

* Update auprc.py

* pre-commit

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: scottgigante-immunai

openproblems/tasks/_cell_cell_communication/_common/metrics/auprc.py

@@ -4,7 +4,10 @@
 
 @metric(
     metric_name="Precision-recall AUC",
-    metric_summary="Area under the precision-recall curve.",
+    metric_summary=(
+        "Area under the precision-recall curve for the binary classification task"
+        " predicting interactions."
+    ),
     paper_reference="davis2006prauc",
     maximize=True,
 )

openproblems/tasks/dimensionality_reduction/methods/pca.py

@@ -38,13 +38,13 @@ def _pca(adata, genes=None):
     return adata
 
 
-@_pca_method(method_name="Principle Component Analysis (PCA) (logCP10k)")
+@_pca_method(method_name="PCA (logCP10k)")
 def pca_logCP10k(adata, test: bool = False):
     adata = log_cp10k(adata)
     return _pca(adata)
 
 
-@_pca_method(method_name="Principle Component Analysis (PCA) (logCP10k, 1kHVG)")
+@_pca_method(method_name="PCA (logCP10k, 1kHVG)")
 def pca_logCP10k_1kHVG(adata, test: bool = False):
     adata = log_cp10k_hvg(adata)
     return _pca(adata, genes=adata.var["highly_variable"])

openproblems/tasks/dimensionality_reduction/methods/tsne.py

@@ -41,17 +41,13 @@ def _tsne(adata, genes=None, test=False, n_pca=50):
     return adata
 
 
-@_tsne_method(
-    method_name="t-Distributed Stochastic Neighbor Embedding (t-SNE) (logCP10k, 1kHVG)"
-)
+@_tsne_method(method_name="t-SNE (logCP10k, 1kHVG)")
 def tsne_logCP10k_1kHVG(adata, test: bool = False, n_pca=50):
     adata = log_cp10k_hvg(adata)
     return _tsne(adata, genes=adata.var["highly_variable"], test=test, n_pca=n_pca)
 
 
-@_tsne_method(
-    method_name="t-Distributed Stochastic Neighbor Embedding (t-SNE) (logCP10k)"
-)
+@_tsne_method(method_name="t-SNE (logCP10k)")
 def tsne_logCP10k(adata, test: bool = False, n_pca=50):
     adata = log_cp10k(adata)
     return _tsne(adata, test=test, n_pca=n_pca)

openproblems/tasks/spatial_decomposition/methods/cell2location.py

@@ -11,7 +11,10 @@
     method_summary=(
         "Cell2location is a decomposition method based on Negative Binomial regression"
         " that is able to account for batch effects in estimating the single-cell gene"
-        " expression signature used for the spatial decomposition step."
+        " expression signature used for the spatial decomposition step. Note that since"
+        " batch information is unavailable in this task, here we use either a"
+        " hard-coded reference, or a negative-binomial learned reference without batch"
+        " labels. The parameter alpha refers to the detection efficiency prior."
     ),
     paper_name="Cell2location maps fine-grained cell types in spatial transcriptomics",
     paper_reference="kleshchevnikov2022cell2location",
@@ -159,9 +162,7 @@ def _cell2location(
     return adata
 
 
-@_cell2location_method(
-    method_name="Cell2location (detection_alpha=20, reference hard-coded)"
-)
+@_cell2location_method(method_name="Cell2location (alpha=20, reference hard-coded)")
 def cell2location_detection_alpha_20(
     adata,
     detection_alpha=20,
@@ -190,9 +191,7 @@ def cell2location_detection_alpha_20(
     )
 
 
-@_cell2location_method(
-    method_name="Cell2location (detection_alpha=1, reference hard-coded)"
-)
+@_cell2location_method(method_name="Cell2location (alpha=1, reference hard-coded)")
 def cell2location_detection_alpha_1(
     adata,
     detection_alpha=1,
@@ -221,9 +220,7 @@ def cell2location_detection_alpha_1(
     )
 
 
-@_cell2location_method(
-    method_name="Cell2location (detection_alpha=20, reference NB without batch info)"
-)
+@_cell2location_method(method_name="Cell2location (alpha=20, NB reference)")
 def cell2location_detection_alpha_20_nb(
     adata,
     detection_alpha=20,
@@ -252,9 +249,7 @@ def cell2location_detection_alpha_20_nb(
     )
 
 
-@_cell2location_method(
-    method_name="Cell2location (detection_alpha=200, reference hard-coded)"
-)
+@_cell2location_method(method_name="Cell2location (alpha=200, reference hard-coded)")
 def cell2location_detection_alpha_200(
     adata,
     detection_alpha=200,
@@ -283,9 +278,7 @@ def cell2location_detection_alpha_200(
     )
 
 
-@_cell2location_method(
-    method_name="Cell2location, amortised (detection_alpha=20, reference hard-coded)"
-)
+@_cell2location_method(method_name="Cell2location (alpha=20, amortised, hard-coded)")
 def cell2location_amortised_detection_alpha_20(
     adata,
     detection_alpha=20,

test/test_core_metadata.py

@@ -10,6 +10,7 @@
 DATASET_SUMMARY_MINLEN = 40
 DATASET_SUMMARY_MAXLEN = 400
 
+METHOD_NAME_MAXLEN = 50
 METHOD_SUMMARY_MINLEN = 40
 METHOD_SUMMARY_MAXLEN = 1000
 
@@ -67,6 +68,7 @@ def test_method_metadata(method):
     assert isinstance(method.metadata["image"], str)
     assert method.metadata["image"].startswith("openproblems")
     assert isinstance(method.metadata["method_name"], str)
+    assert len(method.metadata["method_name"]) < METHOD_NAME_MAXLEN
     assert isinstance(method.metadata["method_summary"], str)
     assert len(method.metadata["method_summary"]) > METHOD_SUMMARY_MINLEN
     assert len(method.metadata["method_summary"]) < METHOD_SUMMARY_MAXLEN