Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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46 lines
1.6 KiB
46 lines
1.6 KiB
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import numpy as np
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import typing
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class Trajectory:
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""" Abstracts the infos about a complete set of trajectories, represented as a numpy array of doubles (the time deltas)
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and a numpy matrix of ints (the changes of states).
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:param list_of_columns: the list containing the times array and values matrix
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:type list_of_columns: List
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:param original_cols_number: total number of cols in the data
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:type original_cols_number: int
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:_actual_trajectory: the trajectory containing also the duplicated/shifted values
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:_times: the array containing the time deltas
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"""
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def __init__(self, list_of_columns: typing.List, original_cols_number: int):
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"""Constructor Method
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"""
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if type(list_of_columns[0][0]) != np.float64:
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raise TypeError('The first array in the list has to be Times')
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self._original_cols_number = original_cols_number
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self._actual_trajectory = np.array(list_of_columns[1:], dtype=np.int).T
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self._times = np.array(list_of_columns[0], dtype=np.float)
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@property
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def trajectory(self) -> np.ndarray:
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return self._actual_trajectory[:, :self._original_cols_number]
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@property
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def complete_trajectory(self) -> np.ndarray:
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return self._actual_trajectory
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@property
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def times(self):
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return self._times
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def size(self):
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return self._actual_trajectory.shape[0]
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def __repr__(self):
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return "Complete Trajectory Rows: " + str(self.size()) + "\n" + self.complete_trajectory.__repr__() + \
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"\nTimes Rows:" + str(self.times.size) + "\n" + self.times.__repr__()
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