diff --git a/CHANGELOG.md b/CHANGELOG.md index f7696eb..971cbfe 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,10 +8,18 @@ and this project adheres to [Semantic Versioning][]. [keep a changelog]: https://keepachangelog.com/en/1.0.0/ [semantic versioning]: https://semver.org/spec/v2.0.0.html +## 0.2.1 (2022-02-16) + +- Warn about joblib, add progress bar postfix str ([#80][]) + +[#80]: https://github.com/YosefLab/scib-metrics/pull/80 + ## 0.2.0 (2022-02-02) - Allow custom nearest neighbors methods in Benchmarker ([#78][]) +[#78]: https://github.com/YosefLab/scib-metrics/pull/78 + ## 0.1.1 (2022-01-04) - Add new tutorial and fix scalability of lisi ([#71][]) diff --git a/pyproject.toml b/pyproject.toml index bd7e405..419c529 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ requires = ["hatchling"] [project] name = "scib-metrics" -version = "0.2.0" +version = "0.2.1" description = "Accelerated and Python-only scIB metrics" readme = "README.md" requires-python = ">=3.8" diff --git a/src/scib_metrics/_nmi_ari.py b/src/scib_metrics/_nmi_ari.py index d5ee88c..a3741a8 100644 --- a/src/scib_metrics/_nmi_ari.py +++ b/src/scib_metrics/_nmi_ari.py @@ -1,4 +1,5 @@ import logging +import warnings from typing import Dict, Tuple import numpy as np @@ -109,7 +110,7 @@ def nmi_ari_cluster_labels_leiden( out = Parallel(n_jobs=n_jobs)(delayed(_compute_nmi_ari_cluster_labels)(X, labels, r) for r in resolutions) except ImportError: - logger.info("Using for loop over resolutions. pip install joblib for parallelization.") + warnings.warn("Using for loop over clustering resolutions. `pip install joblib` for parallelization.") out = [_compute_nmi_ari_cluster_labels(X, labels, r) for r in resolutions] nmi_ari = np.array(out) nmi_ind = np.argmax(nmi_ari[:, 0]) diff --git a/src/scib_metrics/benchmark/_core.py b/src/scib_metrics/benchmark/_core.py index 3d6f493..57589ec 100644 --- a/src/scib_metrics/benchmark/_core.py +++ b/src/scib_metrics/benchmark/_core.py @@ -218,6 +218,7 @@ def benchmark(self) -> None: 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}") metric_fn = getattr(scib_metrics, metric_name) if isinstance(use_metric_or_kwargs, dict): # Kwargs in this case