Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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32 lines
976 B
32 lines
976 B
import numpy as np
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class ConditionalIntensityMatrix:
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def __init__(self, state_residence_times, state_transition_matrix):
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self._state_residence_times = state_residence_times
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self._state_transition_matrix = state_transition_matrix
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#self.cim = np.zeros(shape=(dimension, dimension), dtype=float)
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self._cim = self.state_transition_matrix.astype(np.float)
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def compute_cim_coefficients(self):
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np.fill_diagonal(self._cim, self._cim.diagonal() * -1)
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#print(self._cim)
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self._cim = ((self._cim.T + 1) / (self._state_residence_times + 1)).T
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#np.fill_diagonal(self.state_transition_matrix, 0)
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@property
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def state_residence_times(self):
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return self._state_residence_times
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@property
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def state_transition_matrix(self):
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return self._state_transition_matrix
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@property
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def cim(self):
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return self._cim
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def __repr__(self):
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return 'CIM:\n' + str(self.cim)
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