pymcmcstat.structures package

pymcmcstat.structures.ParameterSet module

Created on Thu Jan 18 10:15:37 2018

@author: prmiles

class pymcmcstat.structures.ParameterSet.ParameterSet(theta=None, ss=None, prior=None, sigma2=None, alpha=None)

Bases: object

Basic MCMC parameter set.

Description: Storage device for passing parameter sets back and forth between sampling methods.

Args:

• theta (ndarray): Sampled values.
• ss (ndarray): Sum-of-squares error(s).
• prior (ndarray): Result from prior function.
• sigma2 (ndarray): Observation errors.
• alpha (float): Result from evaluating likelihood function.

pymcmcstat.structures.ResultsStructure module

Created on Wed Jan 17 09:18:19 2018

@author: prmiles

class pymcmcstat.structures.ResultsStructure.ResultsStructure

Bases: object

Results from MCMC simulation.

Description: Class used to organize results of MCMC simulation.

Attributes:

• export_simulation_results_to_json_file()
• determine_filename()
• save_json_object()
• load_json_object()
• add_basic()
• add_updatesigma()
• add_dram()
• add_prior()
• add_options()
• add_model()
• add_chain()
• add_s2chain()
• add_sschain()
• add_time_stats()
• add_random_number_sequence()

add_basic(nsimu, covariance, parameters, rejected, simutime, theta)

Add basic results from MCMC simulation to structure.

Args:

• nsimu (int): Number of MCMC simulations.
• model (ModelSettings): MCMC model settings.
• covariance (CovarianceProcedures): Covariance variables.
• parameters (ModelParameters): Model parameters.
• rejected (dict): Dictionary of rejection stats.
• simutime (float): Simulation run time in seconds.
• theta (ndarray): Last sampled values.

add_chain(chain=None)

Add chain to results structure.

Args:

• chain (ndarray): Model parameter sampling chain.

add_dram(drscale, RDR, total_rejected, drsettings)

Add results specific to performing DR algorithm.

Args:

• drscale (ndarray): Reduced scale for sampling in DR algorithm. Default is [5,4,3].
• RDR (ndarray): Cholesky decomposition of covariance matrix based on DR.
• total_rejected (int): Number of rejected samples.
• drsettings (DelayedRejection): Need access to counters within DR class.

add_model(model=None)

Saves subset of features of the model settings in a nested dictionary.

Args:

• model (ModelSettings): MCMC model settings.

add_options(options=None)

Saves subset of features of the simulation options in a nested dictionary.

Args:

• options (SimulationOptions): MCMC simulation options.

add_prior(mu, sigma, priortype)

Add results specific to prior function.

Args:

• mu (ndarray): Prior mean.
• sigma (ndarray): Prior standard deviation.
• priortype (int): Flag identifying type of prior.

Note

This feature is not currently implemented.

add_random_number_sequence(rndseq)

Add random number sequence to results structure.

Args:

• rndseq (ndarray): Sequence of sampled random numbers.

Note

This feature is not currently implemented.

add_s2chain(s2chain=None)

Add observiation error chain to results structure.

Args:

• s2chain (ndarray): Sampling chain of observation errors.

add_sschain(sschain=None)

Add sum-of-squares chain to results structure.

Args:

• sschain (ndarray): Calculated sum-of-squares error for each parameter chains set.

add_time_stats(mtime, drtime, adtime)

Add time spend using each sampling algorithm.

Args:

• mtime (float): Time spent performing standard Metropolis.
• drtime (float): Time spent performing Delayed Rejection.
• adtime (float): Time spent performing Adaptation.

Note

This feature is not currently implemented.

add_updatesigma(updatesigma, sigma2, S20, N0)

Add information to results structure related to observation error.

Args:

• updatesigma (bool): Flag to update error variance(s).
• sigma2 (ndarray): Latest estimate of error variance(s).
• S20 (ndarray): Scaling parameter(s).
• N0 (ndarray): Shape parameter(s).

If updatesigma is True, then

results['sigma2'] = np.nan
results['S20'] = S20
results['N0'] = N0

Otherwise

results['sigma2'] = sigma2
results['S20'] = np.nan
results['N0'] = np.nan

classmethod determine_filename(options)

Determine results filename.

If not specified by results_filename in the simulation options, then a default naming format is generated using the date string associated with the initialization of the simulation.

Args:

• options (SimulationOptions): MCMC simulation options.

Returns:

• filename (str): Filename string.

export_simulation_results_to_json_file(results)

Export simulation results to a json file.

Args:

• results (ResultsStructure): Dictionary of MCMC simulation results/settings.

classmethod load_json_object(filename)

Load object stored in json file.

Note

Filename should include extension.

Args:

• filename (str): Load object from file with this name.

Returns:

• results (dict): Object loaded from file.

classmethod save_json_object(results, filename)

Save object to json file.

Note

Filename should include extension.

Args:

• results (dict): Object to save.
• filename (str): Write object into file with this name.