add progress bar arg toBenchmarker (#152)

* add progress bar arg to benchmarker

* add release note

CHANGELOG.md

@@ -10,6 +10,10 @@ and this project adheres to [Semantic Versioning][].
 
 ## 0.6.0 (unreleased)
 
+### Added
+
+-   Add `progress_bar` argument to {class}`scib_metrics.benchmark.Benchmarker` {pr}`152`.
+
 ## 0.5.1 (2024-02-23)
 
 ### Changed

src/scib_metrics/benchmark/_core.py

@@ -115,6 +115,9 @@ class Benchmarker:
         in the prepare step. See the notes below for more information.
     n_jobs
         Number of jobs to use for parallelization of neighbor search.
+    progress_bar
+        Whether to show a progress bar for :meth:`~scib_metrics.benchmark.Benchmarker.prepare` and
+        :meth:`~scib_metrics.benchmark.Benchmarker.benchmark`.
 
     Notes
     -----
@@ -136,6 +139,7 @@ def __init__(
         batch_correction_metrics: Optional[BatchCorrection] = None,
         pre_integrated_embedding_obsm_key: Optional[str] = None,
         n_jobs: int = 1,
+        progress_bar: bool = True,
     ):
         self._adata = adata
         self._embedding_obsm_keys = embedding_obsm_keys
@@ -150,6 +154,7 @@ def __init__(
         self._batch_key = batch_key
         self._label_key = label_key
         self._n_jobs = n_jobs
+        self._progress_bar = progress_bar
 
         self._metric_collection_dict = {
             "Bio conservation": self._bio_conservation_metrics,
@@ -181,7 +186,11 @@ def prepare(self, neighbor_computer: Optional[Callable[[np.ndarray, int], Neighb
             self._emb_adatas[emb_key].obsm[_X_PRE] = self._adata.obsm[self._pre_integrated_embedding_obsm_key]
 
         # Compute neighbors
-        for ad in tqdm(self._emb_adatas.values(), desc="Computing neighbors"):
+        progress = self._emb_adatas.values()
+        if self._progress_bar:
+            progress = tqdm(progress, desc="Computing neighbors")
+
+        for ad in progress:
             if neighbor_computer is not None:
                 neigh_result = neighbor_computer(ad.X, max(self._neighbor_values))
             else:
@@ -208,12 +217,18 @@ def benchmark(self) -> None:
             [sum([v is not False for v in asdict(met_col)]) for met_col in self._metric_collection_dict.values()]
         )
 
-        for emb_key, ad in tqdm(self._emb_adatas.items(), desc="Embeddings", position=0, colour="green"):
-            pbar = tqdm(total=num_metrics, desc="Metrics", position=1, leave=False, colour="blue")
+        progress_embs = self._emb_adatas.items()
+        if self._progress_bar:
+            progress_embs = tqdm(self._emb_adatas.items(), desc="Embeddings", position=0, colour="green")
+
+        for emb_key, ad in progress_embs:
+            pbar = None
+            if self._progress_bar:
+                pbar = tqdm(total=num_metrics, desc="Metrics", position=1, leave=False, colour="blue")
             for metric_type, metric_collection in self._metric_collection_dict.items():
                 for metric_name, use_metric_or_kwargs in asdict(metric_collection).items():
                     if use_metric_or_kwargs:
-                        pbar.set_postfix_str(f"{metric_type}: {metric_name}")
+                        pbar.set_postfix_str(f"{metric_type}: {metric_name}") if pbar is not None else None
                         metric_fn = getattr(scib_metrics, metric_name)
                         if isinstance(use_metric_or_kwargs, dict):
                             # Kwargs in this case
@@ -227,7 +242,7 @@ def benchmark(self) -> None:
                         else:
                             self._results.loc[metric_name, emb_key] = metric_value
                             self._results.loc[metric_name, _METRIC_TYPE] = metric_type
-                        pbar.update(1)
+                        pbar.update(1) if pbar is not None else None
 
         self._benchmarked = True