This rename makes the code easier to type and read.
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@@ -41,7 +41,7 @@ class CollisionAvoid:
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robot.set_left(self.speed)
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await asyncio.sleep(0)
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def get_scaled_sample_around_mean(mean, scale):
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def get_random_sample(mean, scale):
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return mean + (random.uniform(-scale, scale) + random.uniform(-scale, scale)) / 2
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def send_json(data):
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@@ -119,9 +119,9 @@ class Simulation:
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rot1_scale = self.alpha_rot * abs(rot1) + self.alpha_rot_trans * abs(trans)
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trans_scale = self.alpha_trans * abs(trans) + self.alpha_trans_rot * (abs(rot1) + abs(rot2))
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rot2_scale = self.alpha_rot * abs(rot2) + self.alpha_rot_trans * abs(trans)
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rot1_model = np.array([get_scaled_sample_around_mean(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
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trans_model = np.array([get_scaled_sample_around_mean(trans, trans_scale) for _ in range(self.poses.shape[0])])
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rot2_model = np.array([get_scaled_sample_around_mean(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
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rot1_model = np.array([get_random_sample(rot1, rot1_scale) for _ in range(self.poses.shape[0])])
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trans_model = np.array([get_random_sample(trans, trans_scale) for _ in range(self.poses.shape[0])])
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rot2_model = np.array([get_random_sample(rot2, rot2_scale) for _ in range(self.poses.shape[0])])
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return rot1_model, trans_model, rot2_model
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def motion_model(self):
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