Remove sum_to_unity

tsdate/base.py

@@ -134,19 +134,6 @@ def force_probability_space(self, probability_space):
  else:
  logging.warning("Cannot force", *descr)
 
- def sum_to_unity(self, arr):
- """
- Return an array for a node in which the (untransformed) values
- sum to unity
- """
- if self.probability_space == LIN:
- return arr / np.sum(arr)
- elif self.probability_space == LOG:
- with np.errstate(divide="ignore"):
- return np.log(np.exp(arr) / np.sum(np.exp(arr)))
- else:
- raise RuntimeError("Probability space is not", LIN, "or", LOG)
-
  def normalize(self):
  """
  normalize grid and fixed data so the max is one
@@ -229,8 +216,7 @@ def fill_fixed(orig, fixed_data):
  new_obj.fixed_data = fill_fixed(
  self, grid_data if fixed_data is None else fixed_data
  )
- if probability_space is None:
- new_obj.probability_space = self.probability_space
- else:
- new_obj.probability_space = probability_space
+ new_obj.probability_space = self.probability_space
+ if probability_space is not None:
+ new_obj.force_probability_space(probability_space)
  return new_obj

tsdate/core.py

@@ -652,9 +652,9 @@ def inside_pass(self, *, normalize=True, cache_inside=False, progress=None):
  nonfixed_samples = np.intersect1d(inside.nonfixed_node_ids(), self.ts.samples())
  for u in nonfixed_samples:
  # this is in the same probability space as the prior, so we should be
- # OK just to copy the prior values straight in (but we should check they
- # are normalised so that they sum to unity)
- inside[u][:] = self.priors.sum_to_unity(self.priors[u])
+ # OK just to copy the prior values straight in. It's unclear to me (Yan)
+ # how/if they should be normalised, however
+ inside[u][:] = self.priors[u]
 
  if cache_inside:
  g_i = np.full(