"""
Config Module :mod:`ui.config`
---------------------------------------------------------------
:mod:`!ui.config` is used to create instances of the different building blocks for a ProbReM project, e.g. the PRM model, the data interface, the learner and the inference methods. The methods are accessed by importing the `config` module ::
from ui import config
import probrem
config.loadPRM(prmSpec)
Then code above for example would initialize the PRM module :mod:`~!prm.prm`::
print probrem.PRM
<module 'prm.prm' from './../../src/prm/prm.pyc'>
The config module can't be executed directly.
"""
import sys
from ui import log
import logging
from xml_prm.parser import DataInterfaceParser
from xml_prm.parser import PRMparser
import learners
from inference import engine
[docs]def fromFile(probremI, config):
'''Using a config file to load PRM. Not implemented yet. '''
raise Exception("Config file support not implemented yet")
[docs]def loadPRM(prmSpec):
"""
Loads a :class:`~!prm.prm.PRM` instance using the :class:`.PRMparser`
:arg prmSpec: File name of PRM XML specification
:returns: :class:`prm.prm.PRM` instance
"""
logging.info("PRM Factory: create PRM from %s"%(prmSpec.split('/')[-1]))
return PRMparser().parsePRM(prmSpec)
[docs]def loadDI(diSpec):
"""
Loads a :class:`~!data.datainterface.DataInterface` instance
:arg diSpec: File name of Data Interface XML specification
:returns: :class:`data.datainterface.DataInterface` instance, e.g. :class:`~data.sqliteinterface.SQLiteDI`
"""
logging.info("DataInterface Factory: create DataInterface from %s"%(diSpec.split('/')[-1]))
return DataInterfaceParser().parseDataInterface(diSpec)
[docs]def loadLearner(learnerType):
"""
Loads a learner instance, e.g. a :class:`~!learners.cpdlearners.CPDLearner` instance for learning
the conditional probability distributions (CPDs).
:arg learnerType: Name of a learner class (e.g. `CPDTabularLearner`)
:returns: A learner instance, e.g. :class:`~learners.cpdlearners.CPDTabularLearner`
"""
logging.info('Learner Factory: create %s'%(learnerType))
return getattr(learners,learnerType )()
[docs]def loadInferenceAlgorithm(inferenceType):
"""
Loads the specified inference algorithm for the engine :mod:`~!.engine` and configures it to use `inferenceType` (e.g. MCMC,LW).
Usually an inference algorithm implements a `configure()` method that can be used to
precompute data structures needed for inference.
In the case of the Gibbs sampler, :mod:`.gibbs.configure` will precompute all the conditional likelihood
functions of the attributes with parents. Note that at the time a inference method is configured,
the PRM should be initialized with proper local distributions (either learned or loaded).
:arg inferenceType: The name of the inference method (e.g. `GIBBS` or `MH`)
"""
if inferenceType == 'GIBBS':
from inference.mcmc import gibbs
engine.inferenceAlgo = gibbs
gibbs.configure()
elif inferenceType == 'MH':
from inference.mcmc import mh
engine.inferenceAlgo = mh
mh.configure()