made PriorDict hashable and fixed caching

bilby/core/prior/dict.py

@@ -381,15 +381,20 @@ class PriorDict(dict):
 
     @lru_cache()
     def normalize_constraint_factor(self, keys):
-        min_accept = 50
-        sampling_chunk = 250
+        min_accept = 1000
+        sampling_chunk = 5000
         samples = self.sample_subset(keys=keys, size=sampling_chunk)
-        keep = np.array(self.evaluate_constraints(samples))
+        keep = np.atleast_1d(self.evaluate_constraints(samples))
+        if len(keep) == 1:
+            return 1
+        all_samples = {key: np.array([]) for key in keys}
+        _first_key = list(all_samples.keys())[0]
         while np.count_nonzero(keep) < min_accept:
-            new_samples = self.sample_subset(keys=keys, size=sampling_chunk)
+            samples = self.sample_subset(keys=keys, size=sampling_chunk)
             for key in samples:
-                samples[key] = np.hstack([samples[key], new_samples[key]])
-            keep = np.array(self.evaluate_constraints(samples))
+                all_samples[key] = np.hstack(
+                    [all_samples[key], samples[key].flatten()])
+            keep = np.array(self.evaluate_constraints(all_samples), dtype=bool)
         return len(keep) / np.count_nonzero(keep)
 
     def prob(self, sample, **kwargs):