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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/main_package/classes/trajectory.py

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import numpy as np
class Trajectory:
"""
Rappresenta una traiettoria come un numpy_array contenente n-ple (indx, T_k,S_i,.....,Sj)
Offre i metodi utili alla computazione sulla struttura stessa.
Una Trajectory viene costruita a partire da una lista di numpyarray dove ogni elemento rappresenta una colonna
della traj
:actual_trajectory: il numpy_array contenente la successione di n-ple (indx, T_k,S_i,.....,Sj)
"""
def __init__(self, list_of_columns, original_cols_number):
if type(list_of_columns[0][0]) != np.float64:
raise TypeError('The first array in the list has to be Times')
self.original_cols_number = original_cols_number
self._actual_trajectory = np.array(list_of_columns[1:], dtype=np.int).T
self._times = np.array(list_of_columns[0], dtype=np.float)
@property
def trajectory(self):
return self._actual_trajectory[:, :self.original_cols_number]
@property
def complete_trajectory(self):
return self._actual_trajectory
@property
def times(self):
return self._times
def size(self):
return self._actual_trajectory.shape[0]
def __repr__(self):
return "Complete Trajectory Rows: " + str(self.size()) + "\n" + self.complete_trajectory.__repr__() + \
"\nTimes Rows:" + str(self.times.size) + "\n" + self.times.__repr__()