mixture¶

class
mics.
mixture
(samples, engine)[source]¶ A mixture of independently collected samples (MICS).
Parameters:  samples (
pooledsample
or list(sample
)) – A list of samples.  engine (
MICS
orMBAR
) – A method for mixturemodel analysis.

free_energies
(reference=0)[source]¶ Computes the free energies of all sampled states relative to a given reference state, as well as their standard errors.
Parameters: reference (int, optional, default=0) – Specifies which sampled state will be considered as a reference for computing freeenergy differences. Returns: pandas.DataFrame – A data frame containing the freeenergy differences and their computed standard errors for all sampled states.

reweighting
(potential, properties={}, derivatives={}, combinations={}, conditions={}, reference=0, **constants)[source]¶ Computes averages of specified properties at target states defined by a given reduced potential function with distinct passed parameter values, as well as the free energies of such states with respect to a sampled reference state. Also, computes derivatives of these averages and free energies with respect to the mentioned parameters. In addition, evaluates combinations of free energies, averages, and derivatives. In all cases, uncertainty propagation is handled automatically by means of the delta method.
Parameters:  potential (str) – A mathematical expression defining the reduced potential of the target states. It might depend on the collective variables of the mixture samples, as well as on external parameters whose values will be passed via conditions or constants, such as explained below.
 properties (dict(str: str), optional, default={}) – A dictionary associating names to mathematical expressions, thus defining a set of properties whose averages must be evaluated at the target states. If it is omitted, then only the relative free energies of the target states will be evaluated. The expressions might depend on the same collective variables and parameters mentioned above for potential.
 derivatives (dict(str: (str, str)), optional, default={}) – A dictionary associating names to (property, parameter) pairs, thus specifying derivatives of average properties at the target states or relative free energies of these states with respect to external parameters. For each pair, property must be either “f” (for free energy) or a name defined in properties, while parameter must be an external parameter such as described above for potential.
 combinations (dict(str: str), optional, default={}) – A dictionary associating names to mathematical expressions, thus defining combinations among average properties at the target states, the relative free energies of these states, and their derivatives with respect to external parameters. The expressions might depend on “f” (for free energy) or on the names defined in properties, as well as on external parameters such as described above for potential.
 conditions (pandas.DataFrame or dict, optional, default={}) – A data frame whose column names are external parameters present in mathematical expressions specified in arguments potential, properties, and combinations. The rows of the data frame contain sets of values of these parameters, in such as way that the reweighting is carried out for every single set. This is a way of defining multiple target states from a single potential expression. The same information can be passed as a dictionary associating names to lists of numerical values, provided that all lists are equally sized. If it is empty, then a unique target state will be considered and all external parameters in potential, if any, must be passed as keyword arguments.
 reference (int, optional, default=0) – The index of a sampled state to be considered as a reference for computing relative free energies.
 **constants (keyword arguments) – A set of keyword arguments passed as name=value, aimed to define external parameter values for the evaluation of mathematical expressions. These values will be repeated at all target states specified via potential and conditions.
Returns: pandas.DataFrame – A data frame containing the computed quantities, along with their estimated uncertainties, at all target states specified via potential and conditions.
 samples (