From b63e0e900dbb12f417fa8b07b88419fd177af48d Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Sun, 28 Sep 2025 20:49:01 +0200 Subject: [PATCH] refactor(qav3): cleanup MO _get_n_clusters MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index c77abe9..eb52e4f 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -857,14 +857,11 @@ class QuickAdapterRegressorV3(BaseRegressionModel): if n_samples <= 1: return 1 n_uniques = np.unique(matrix, axis=0).shape[0] - upper_bound = max(1, min(max_n_clusters, n_uniques, n_samples)) - lower_bound = max(2, min(min_n_clusters, upper_bound)) + upper_bound = min(max_n_clusters, n_uniques, n_samples) if upper_bound < 2: return 1 - try: - n_clusters = int(round(np.log2(max(n_samples, 2)))) - except Exception: - n_clusters = min_n_clusters + lower_bound = min(min_n_clusters, upper_bound) + n_clusters = int(round(np.log2(max(n_uniques, 2)))) return max(lower_bound, min(n_clusters, upper_bound)) if metric in { -- 2.43.0