code: def test_parametrization(self):
      err_msg = "`m` and `L`, if provided, must be sequences with one element per active dimension"
  
      with pytest.raises(ValueError, match="Provide one of `c` or `L`"):
          cov_func = pm.gp.cov.ExpQuad(1, ls=0.1)
          pm.gp.HSGP(m=[500], c=2, L=[12], cov_func=cov_func)
  
      with pytest.raises(ValueError, match=err_msg):
          # m must be a list
          cov_func = pm.gp.cov.ExpQuad(1, ls=0.1)
          pm.gp.HSGP(m=500, c=2, cov_func=cov_func)
  
      with pytest.raises(ValueError, match=err_msg):
          # m must have same length as L
          cov_func = pm.gp.cov.ExpQuad(2, ls=[1, 2])
          pm.gp.HSGP(m=[500], L=[12, 12], cov_func=cov_func)
  
      with pytest.raises(ValueError, match=err_msg):
          # m must have same length as L, and match number of active dims of cov_func
          cov_func = pm.gp.cov.ExpQuad(1, ls=0.1)
          pm.gp.HSGP(m=[500], L=[12, 12], cov_func=cov_func)
  
      with pytest.raises(
          ValueError,
          match="`parameterization` must be either 'centered' or 'noncentered'.",
      ):
          cov_func = pm.gp.cov.ExpQuad(2, ls=[1, 2])
          pm.gp.HSGP(
              m=[50, 50],
              L=[12, 12],
              parameterization="wrong",
              cov_func=cov_func,
          )
  
      # pass without error, cov_func has 2 active dimensions, c given as scalar
      cov_func = pm.gp.cov.ExpQuad(3, ls=[1, 2], active_dims=[0, 2])
      pm.gp.HSGP(m=[50, 50], c=2, cov_func=cov_func)
  
      # pass without error, all have two dimensions
      cov_func = pm.gp.cov.ExpQuad(2, ls=[1, 2])
      pm.gp.HSGP(m=[50, 50], L=[12, 12], cov_func=cov_func)
  
imports: import arviz
  import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  from scipy.spatial import distance
  import pymc
label_desc: Use image node_id 3 for calling the TestHSGP obj's underlying member method code with example usage: obj.test_parametrization() without return types