def remove_outliers(points, outliers): return points[~outliers]

Here's a feature idea:

Automatic Outlier Detection and Removal

def detect_outliers(points, threshold=3): mean = np.mean(points, axis=0) std_dev = np.std(points, axis=0) distances = np.linalg.norm(points - mean, axis=1) outliers = distances > (mean + threshold * std_dev) return outliers