Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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40 lines
1.2 KiB
40 lines
1.2 KiB
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import numpy as np
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class Trajectory:
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"""
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Rappresenta una traiettoria come un numpy_array contenente n-ple (indx, T_k,S_i,.....,Sj)
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Offre i metodi utili alla computazione sulla struttura stessa.
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Una Trajectory viene costruita a partire da una lista di numpyarray dove ogni elemento rappresenta una colonna
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della traj
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:actual_trajectory: il numpy_array contenente la successione di n-ple (indx, T_k,S_i,.....,Sj)
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"""
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def __init__(self, list_of_columns, original_cols_number):
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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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#TODO valutare se vale la pena ordinare la lista di numpy array per tipo
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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):
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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):
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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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