class_docstr: The abstract class provides the basic structure for all model components
  
  Methods:
      createEvaluation: create the initial evaluation matrix
      createTransition: create the initial transition matrix
      createCovPrior: create a simple prior covariance matrix
      createMeanPrior: create a simple prior latent state
      checkDimensions: if user supplies their own covPrior and meanPrior, this can 
                       be used to check if the dimension matches
class_docstr_tok: ["The","abstract","class","provides","the","basic","structure","for","all","model","components","Methods",":","createEvaluation",":","create","the","initial","evaluation","matrix","createTransition",":","create","the","initial","transition","matrix","createCovPrior",":","create","a","simple","prior","covariance","matrix","createMeanPrior",":","create","a","simple","prior","latent","state","checkDimensions",":","if","user","supplies","their","own","covPrior","and","meanPrior",",","this","can","be","used","to","check","if","the","dimension","matches"]
docstr: Check if a and b are equal or both are None
docstr_tok: ["Check","if","a","and","b","are","equal","or","both","are","None"]
code: def equalOrNone(self, a, b):
      """Check if a and b are equal or both are None"""
      return (a is None and b is None) or a == b
  
file_path: pydlm/pydlm/modeler/component.py
imports: from abc import ABCMeta, abstractmethod
label_desc: Use image node_id 8 for calling the component obj's underlying member method code with example usage: obj.equalOrNone(a, b) and returns: unknown