code: def evaluate(self, t, theta):
      t = np.asarray(t)
      with warnings.catch_warnings():
          warnings.simplefilter("ignore", RuntimeWarning)
          val = -(np.log(-expm1(-theta * t)) - np.log(-expm1(-theta)))
      return val
  
imports: import warnings
  import numpy
  from scipy.special import expm1, gamma
label_desc: Use image node_id 1 for calling the TransfFrank obj's underlying member method code with example usage: obj.evaluate(t, theta) and returns: val