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Cleanup and refactoring (#171)
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Gal Leibovich
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@@ -84,7 +84,8 @@ class DFPAlgorithmParameters(AlgorithmParameters):
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"""
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:param num_predicted_steps_ahead: (int)
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Number of future steps to predict measurements for. The future steps won't be sequential, but rather jump
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in multiples of 2. For example, if num_predicted_steps_ahead = 3, then the steps will be: t+1, t+2, t+4
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in multiples of 2. For example, if num_predicted_steps_ahead = 3, then the steps will be: t+1, t+2, t+4.
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The predicted steps will be [t + 2**i for i in range(num_predicted_steps_ahead)]
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:param goal_vector: (List[float])
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The goal vector will weight each of the measurements to form an optimization goal. The vector should have
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