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| import numpy as np
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| from scipy.spatial.transform import Rotation
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| def angle_3p(a, b, c):
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| """
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| Calculate the angle between three points in a 2D space.
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| Args:
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| a (list or array-like): The coordinates of the first point.
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| b (list or array-like): The coordinates of the second point.
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| c (list or array-like): The coordinates of the third point.
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| Returns:
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| float: The angle in degrees (0, 180) between the vectors
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| from point a to point b and point b to point c.
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| """
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| a = np.array(a)
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| b = np.array(b)
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| c = np.array(c)
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| ab = b - a
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| bc = c - b
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| dot_product = np.dot(ab, bc)
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| norm_ab = np.linalg.norm(ab)
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| norm_bc = np.linalg.norm(bc)
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| cos_theta = np.clip(dot_product / (norm_ab * norm_bc + 1e-4), -1, 1)
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| theta_radians = np.arccos(cos_theta)
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| theta_degrees = np.degrees(theta_radians)
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| return theta_degrees
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| def random_transform(
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| points, max_translation=1.0, apply_augmentation=False, centralize=True
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| ) -> np.ndarray:
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| """
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| Randomly transform a set of 3D points.
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| Args:
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| points (numpy.ndarray): The points to be transformed, shape=(N, 3)
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| max_translation (float): The maximum translation value. Default is 1.0.
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| apply_augmentation (bool): Whether to apply random rotation/translation on ref_pos
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| Returns:
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| numpy.ndarray: The transformed points.
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| """
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| if centralize:
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| points = points - points.mean(axis=0)
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| if not apply_augmentation:
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| return points
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| translation = np.random.uniform(-max_translation, max_translation, size=3)
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| R = Rotation.random().as_matrix()
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| transformed_points = np.dot(points + translation, R.T)
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| return transformed_points
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|
