From de7b5503c6513a3d1c88248d6df8f86429942d5e Mon Sep 17 00:00:00 2001 From: nieves Date: Wed, 20 Sep 2023 20:23:39 +0200 Subject: [PATCH] style changes --- ctapipe/image/cleaning.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/ctapipe/image/cleaning.py b/ctapipe/image/cleaning.py index 91c96a307ba..5d19cf292b1 100644 --- a/ctapipe/image/cleaning.py +++ b/ctapipe/image/cleaning.py @@ -125,8 +125,10 @@ def time_clustering( d_scale=0.25, ): """ + Clean an image by selecting pixels which pass a time clustering algorithm using DBSCAN. Previously used for HESS [timecleaning]_. + Parameters ---------- geom: `ctapipe.instrument.CameraGeometry` @@ -162,8 +164,7 @@ def time_clustering( X = np.column_stack((time[precut_mask] / t_scale, pix_x, pix_y)) - db = DBSCAN(eps=eps, min_samples=minpts).fit(X) - labels = db.labels_ + labels = DBSCAN(eps=eps, min_samples=minpts).fit_predict(X) # no_clusters = len(np.unique(labels))-1 # Could be used for gh separation @@ -624,7 +625,7 @@ class TimeCleaner(ImageCleaner): def __call__( self, tel_id: int, image: np.ndarray, arrival_times=None ) -> np.ndarray: - """Apply FACT-style image cleaning. see ImageCleaner.__call__()""" + """Apply HESS image cleaning. see ImageCleaner.__call__()""" return time_clustering( geom=self.subarray.tel[tel_id].camera.geometry, image=image,