class_docstr: Compare TP with high degrees of freedom to GP
class_docstr_tok: ["Compare","TP","with","high","degrees","of","freedom","to","GP"]
code: def testTPvsLatent(self):
      with pm.Model() as model:
          scale_func = pm.gp.cov.ExpQuad(3, [0.1, 0.2, 0.3])
          tp = pm.gp.TP(scale_func=scale_func, nu=self.nu)
          f = tp.prior("f", self.X, reparameterize=False)
          p = tp.conditional("p", self.Xnew)
      assert tuple(f.shape.eval()) == (self.X.shape[0],)
      assert tuple(p.shape.eval()) == (self.Xnew.shape[0],)
      tp_logp = model.compile_logp()({"f": self.y, "p": self.pnew})
      npt.assert_allclose(
          self.gp_latent_logp, tp_logp, atol=0, rtol=1e-2
      )
  
imports: from functools import reduce
  from operator import add
  import numpy
  import numpy.testing
  import pytest
  import pymc
  from pymc.math import cartesian
label_desc: Use image node_id 2 for calling the TestTP obj's underlying member method code with example usage: obj.testTPvsLatent() without return types