MissedEventsG¶
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class
dcprogs.likelihood.
MissedEventsG
(*args, **kwargs)[source]¶ Computes missed-events likelihood.
Exact calculations take place for times smaller than nmaxτ. Asymptotic calculations take over for larger times.
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af
(self, t) → DCProgs::t_rmatrix[source]¶ Likelihood of an observed open time of length
t
Parameters: t – A scalar or something to a numpy array. In the latter case, the return is an array of matrices.
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af_factor
¶ Factor accounting for minimum shut time
It is the likelihood QAFe−QFFτ of a shut time of length τ.
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fa
(self, t) → DCProgs::t_rmatrix[source]¶ Likelihood of a shut time of length
t
Parameters: t – A scalar or something to a numpy array. In the latter case, the return is an array of matrices.
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fa_factor
¶ Factor accounting for minimum open time
It is the likelihood QFAe−QAAτ of an open time of length τ.
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final_occupancies
¶ Equilibrium occupancies for final states.
Computes the right eigenvector of eGFAeGAF, where eGFA is the laplacian for s=0 of the likelihood.
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initial_occupancies
¶ Equilibrium occupancies for initial states.
Computes the left eigenvector of eGAFeGFA, where eGAF is the laplacian for s=0 of the likelihood.
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laplace_af
(self, s) → DCProgs::t_rmatrix[source]¶ Exact missed-events G in Laplace space.
The exact expression is eGAF(s)=AR(s)e−sτQAFeQFFτ, with AR(s)=[sI−QAA−QAF∫τ0e−steQFFt∂tQFA]−1.
Parameters: s – The laplace scale. A real scalar or something convertible to a numpy array. Returns: A matrix if the input is scalar, an array of matrices otherwise, with the shape of the input.
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laplace_fa
(self, s) → DCProgs::t_rmatrix[source]¶ Exact missed-events G in Laplace space.
The exact expression is eGFA(s)=FR(s)e−sτQFAeQAAτ, with FR(s)=[sI−QFF−QFA∫τ0e−steQAAt∂tQAF]−1.
Parameters: s – The laplace scale. A real scalar or something convertible to a numpy array. Returns: A matrix if the input is scalar, an array of matrices otherwise, with the shape of the input.
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nmax
¶ Cut-off time of exact calculations in units of tau.
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nopen
¶ Number of open-states.
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nshut
¶ Number of shut-states.
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tau
¶ Resolution or maximum length of the missed events.
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tmax
¶ Cut-off time of exact calculations tmax=(nmax−1)tau.
For practical reasons, the minimum observation time has alreadybeen removed here.
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