Change data format to only use structured arrays to avoid data loader…

… mess.

alea/blueice_extended_model.py

@@ -8,6 +8,7 @@
 import scipy.stats as stats
 from blueice.likelihood import LogAncillaryLikelihood
 from blueice.likelihood import LogLikelihoodSum
+from inference_interface import dict_to_structured_array, structured_array_to_dict
 
 
 class BlueiceExtendedModel(StatisticalModel):
@@ -155,7 +156,7 @@ def _generate_data(self, **generate_values) -> list:
         generate_values_anc = {k: v for k, v in generate_values.items() if k in ancillary_keys}
         ancillary_measurements = self._generate_ancillary_measurements(
             **generate_values_anc)
-        return science_data + [ancillary_measurements] + [generate_values]
+        return science_data + [ancillary_measurements] + [dict_to_structured_array(generate_values)]
 
     def _generate_science_data(self, **generate_values) -> list:
         science_data = [gen.simulate(**generate_values)
@@ -177,7 +178,7 @@ def _generate_ancillary_measurements(self, **generate_values) -> dict:
                     parameter_meas = param.fit_limits[1]
             ancillary_measurements[name] = parameter_meas
 
-        return ancillary_measurements
+        return dict_to_structured_array(ancillary_measurements)
 
 
 class CustomAncillaryLikelihood(LogAncillaryLikelihood):
@@ -215,16 +216,16 @@ def constraint_terms(self) -> dict:
         """
         return {name: func.logpdf for name, func in self.constraint_functions.items()}
 
-    def set_data(self, d: dict):
+    def set_data(self, d: np.array):
         """
         Set the data of the ancillary likelihood (ancillary measurements).
 
         Args:
-            d (dict): Data in this case is a dict of ancillary measurements.
+            d (np.array): Data of ancillary measurements, stored as numpy array
         """
         # This results in shifted constraint terms.
-        assert set(d.keys()) == set(self.parameters.names)
-        self.constraint_functions = self._get_constraint_functions(**d)
+        assert set(d.dtype.names) == set(self.parameters.names)
+        self.constraint_functions = self._get_constraint_functions(**structured_array_to_dict(d))
 
     def ancillary_likelihood_sum(self, evaluate_at: dict) -> float:
         """Return the sum of all constraint terms.