Source code for paramonte._SpecDRAM

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####   ParaMonte: plain powerful parallel Monte Carlo library.
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import numpy as np
from _SpecBase import inputFileDelim

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#### SpecDRAM specification type-checking class
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[docs]def adaptiveUpdateCount(adaptiveUpdateCount): if isinstance(adaptiveUpdateCount,int): return "adaptiveUpdateCount=" + str(adaptiveUpdateCount) + inputFileDelim else: raise TypeError("The input specification, adaptiveUpdateCount, must be of type int.")
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[docs]def adaptiveUpdatePeriod(adaptiveUpdatePeriod): if isinstance(adaptiveUpdatePeriod,int): return "adaptiveUpdatePeriod=" + str(adaptiveUpdatePeriod) + inputFileDelim else: raise TypeError("The input specification, adaptiveUpdatePeriod, must be of type int.")
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[docs]def greedyAdaptationCount(greedyAdaptationCount): if isinstance(greedyAdaptationCount,int): return "greedyAdaptationCount=" + str(greedyAdaptationCount) + inputFileDelim else: raise TypeError("The input specification, greedyAdaptationCount, must be of type int.")
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[docs]def delayedRejectionCount(delayedRejectionCount): if isinstance(delayedRejectionCount,int): return "delayedRejectionCount=" + str(delayedRejectionCount) + inputFileDelim else: raise TypeError("The input specification, delayedRejectionCount, must be of type int.")
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[docs]def burninAdaptationMeasure(burninAdaptationMeasure): if isinstance(burninAdaptationMeasure,(int,float)): return "burninAdaptationMeasure=" + str(burninAdaptationMeasure) + inputFileDelim else: raise TypeError("The input specification, burninAdaptationMeasure, must be of type float.")
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[docs]def delayedRejectionScaleFactorVec(delayedRejectionScaleFactorVec): if isinstance(delayedRejectionScaleFactorVec,(list,tuple,np.ndarray)): return "delayedRejectionScaleFactorVec=" + str(np.array(list(delayedRejectionScaleFactorVec)).flatten()).strip('[]') + inputFileDelim else: raise TypeError("The input specification, delayedRejectionScaleFactorVec must be list, tuple, or numpy vector of ndim or less elements of type float.")
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[docs]def helpme(specification = ""): """ | Return help on the input ParaDRAM specification. If no input is provided, then the web-link to the entire list of ParaDRAM specifications will be output. **Parameters** specification A string that can take be any of the simulation specifications of a ParaDRAM object, such as, ``"chainSize"``, ``"sampleSize"``, ... **Returns** None """ import _paramonte as pm if isinstance(specification,str): if specification!="": specification = "#" + specification.lower() else: pm.abort( msg = "The input argument to helpme() function must be a string whose value \n" + "can be the name of one of the specifications of the ParaDRAM sampler.\n" + "For example, to get information about the variable `chainSize`, try:\n\n" + " pmpd.spec.helpme(\"chainSize\")\n\n" + "where ``pmpd`` is the name of the ParaDRAM sampler object.\n" + "For more information and examples on the usage, visit:\n\n" + " " + pm.website.home.url , methodName = pm.names.paradram , marginTop = 1 , marginBot = 1 ) print("Visit: " + pm.website.home.usage.paradram.specifications.url + specification)
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