pyemma.thermo.StationaryModel¶
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class
pyemma.thermo.
StationaryModel
(pi=None, f=None, normalize_energy=True, label='ground state')¶ StationaryModel combines a stationary vector with discrete-state free energies.
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__init__
(pi=None, f=None, normalize_energy=True, label='ground state')¶ StationaryModel combines a stationary vector with discrete-state free energies.
Parameters: - pi (ndarray(n)) – Stationary distribution. If not already normalized, pi will be scaled to fulfill \(\sum_i \pi_i = 1\). The free energies f will be computed from pi via \(f_i = - \log(\pi_i)\). Only if normalize_f is True, a constant will be added to ensure consistency with \(\sum_i \pi_i = 1\).
- f (ndarray(n)) – Discrete-state free energies. If normalized_f = True, a constant will be added to normalize the stationary distribution. Otherwise f is left as given. If both (pi and f) are given, f takes precedence.
- normalize_energy (bool, default=True) – If parametrized by free energy f, normalize them such that \(\sum_i \pi_i = 1\), which is achieved by \(\log \sum_i \exp(-f_i) = 0\).
- label (str, default='ground state') – Human-readable description for the thermodynamic state of this model. May contain a temperature description, such as ‘300 K’ or a description of bias energy such as ‘unbiased’ or ‘Umbrella 1’
Methods
__init__
([pi, f, normalize_energy, label])StationaryModel combines a stationary vector with discrete-state free energies. expectation
(a)Equilibrium expectation value of a given observable. get_model_params
([deep])Get parameters for this model. set_model_params
([pi, f, normalize_f, label])Call to set all basic model parameters. update_model_params
(**params)Update given model parameter if they are set to specific values Attributes
active_set
The active set of states on which all computations and estimations will be done. f
The free energies (in units of kT) on the configuration states. f_full_state
free_energies
The free energies (in units of kT) on the configuration states. free_energies_full_state
label
Human-readable description for the thermodynamic state of this model. nstates
Number of active states on which all computations and estimations are done. nstates_full
Size of the full set of states. pi
The stationary distribution on the configuration states. pi_full_state
stationary_distribution
The stationary distribution on the configuration states. stationary_distribution_full_state
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active_set
¶ The active set of states on which all computations and estimations will be done.
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expectation
(a)¶ Equilibrium expectation value of a given observable.
Parameters: a ((M,) ndarray) – Observable vector Returns: val – Equilibrium expectation value of the given observable Return type: float Notes
The equilibrium expectation value of an observable a is defined as follows
\[\mathbb{E}_{\mu}[a] = \sum_i \mu_i a_i\]\(\mu=(\mu_i)\) is the stationary vector of the transition matrix \(T\).
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f
¶ The free energies (in units of kT) on the configuration states.
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free_energies
¶ The free energies (in units of kT) on the configuration states.
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get_model_params
(deep=True)¶ Get parameters for this model.
Parameters: deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns: params – Parameter names mapped to their values. Return type: mapping of string to any
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label
¶ Human-readable description for the thermodynamic state of this model.
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nstates
¶ Number of active states on which all computations and estimations are done.
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nstates_full
¶ Size of the full set of states.
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pi
¶ The stationary distribution on the configuration states.
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set_model_params
(pi=None, f=None, normalize_f=None, label=None)¶ Call to set all basic model parameters.
Parameters: - pi (ndarray(n)) – Stationary distribution. If not already normalized, pi will be scaled to fulfill \(\sum_i \pi_i = 1\). The free energies f will then be computed from pi via \(f_i = - \log(\pi_i)\).
- f (ndarray(n)) – Discrete-state free energies. If normalized_f = True, a constant will be added to normalize the stationary distribution. Otherwise f is left as given. Then, pi will be computed from f via \(\pi_i = \exp(-f_i)\) and, if necessary, scaled to fulfill \(\sum_i \pi_i = 1\). If both (pi and f) are given, f takes precedence over pi.
- normalize_energy (bool, default=True) – If parametrized by free energy f, normalize them such that \(\sum_i \pi_i = 1\), which is achieved by \(\log \sum_i \exp(-f_i) = 0\).
- label (str, default=None) – Human-readable description for the thermodynamic state of this model. May contain a temperature description, such as ‘300 K’ or a description of bias energy such as ‘unbiased’ or ‘Umbrella 1’.
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stationary_distribution
¶ The stationary distribution on the configuration states.
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update_model_params
(**params)¶ Update given model parameter if they are set to specific values
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