class_docstr: The baseModel class that provides the basic model structure for dlm. 
  
  Attributes:
      transition: the transition matrix G
      evaluation: the evaluation F
      noiseVar: the variance of the observation noise
      sysVar: the covariance of the underlying states
      innovation: the incremnent of the latent covariance W
      state: the latent states
      df: the degree of freedom (= number of data points)
      obs: the expectation of the observation
      obsVar: the variance of the observation
  
  Methods:
      initializeObservation: initialize the obs and obsVar
      validation: validate the matrix dimensions are consistent.
docstr: Validate the model components are consistent
  
          
docstr_tok: ["Validate","the","model","components","are","consistent"]
code: def validation(self):
      """Validate the model components are consistent"""
      # check symmetric
      tl.checker.checkSymmetry(self.transition)
      tl.checker.checkSymmetry(self.sysVar)
      if self.innovation is not None:
          tl.checker.checkSymmetry(self.innovation)
  
      # check wether dimension match
      tl.checker.checkMatrixDimension(self.transition, self.sysVar)
      if self.innovation is not None:
          tl.checker.checkMatrixDimension(
              self.transition, self.innovation
          )
      tl.checker.checkVectorDimension(self.evaluation, self.transition)
      tl.checker.checkVectorDimension(self.state, self.transition)
  
imports: import numpy
  import pydlm.base.tools
label_desc: Use image node_id 3 for calling the baseModel obj's underlying member method code with example usage: obj.validation() without return types