diff --git a/micro_manager/adaptivity/adaptivity.py b/micro_manager/adaptivity/adaptivity.py
index ec9b31b0..ae2b9411 100644
--- a/micro_manager/adaptivity/adaptivity.py
+++ b/micro_manager/adaptivity/adaptivity.py
@@ -53,7 +53,7 @@ def _get_similarity_dists(self, dt: float, similarity_dists: np.ndarray, data: d
         _similarity_dists = np.copy(similarity_dists)
 
         data_diff = np.zeros_like(_similarity_dists)
-        for name in self._adaptivity_data_names:
+        for name in data.keys():
             data_vals = data[name]
             if data_vals.ndim == 1:
                 # If the adaptivity-data is a scalar for each simulation,
diff --git a/micro_manager/adaptivity/global_adaptivity.py b/micro_manager/adaptivity/global_adaptivity.py
index c217b8a6..155853a7 100644
--- a/micro_manager/adaptivity/global_adaptivity.py
+++ b/micro_manager/adaptivity/global_adaptivity.py
@@ -94,9 +94,15 @@ def compute_adaptivity(
         is_sim_active : numpy array
             1D array having state (active or inactive) of each micro simulation
         """
+        for name in data_for_adaptivity.keys():
+            if name not in self._adaptivity_data_names:
+                raise ValueError(
+                    "Data for adaptivity must be one of the following: {}".format(
+                        self._adaptivity_data_names.keys()))
+
         # Gather adaptivity data from all ranks
         global_data_for_adaptivity = dict()
-        for name in self._adaptivity_data_names.keys():
+        for name in data_for_adaptivity.keys():
             data_as_list = self._comm.allgather(data_for_adaptivity[name])
             global_data_for_adaptivity[name] = np.concatenate((data_as_list[:]), axis=0)
 
@@ -106,14 +112,9 @@ def compute_adaptivity(
 
         is_sim_active, sim_is_associated_to = self._update_inactive_sims(
             similarity_dists, is_sim_active, sim_is_associated_to_nm1, micro_sims)
-
-        print("sim_is_associated_to: {}".format(sim_is_associated_to))
-
         sim_is_associated_to = self._associate_inactive_to_active(
             similarity_dists, is_sim_active, sim_is_associated_to)
 
-        print("sim_is_associated_to: {}".format(sim_is_associated_to))
-
         self._logger.info(
             "{} active simulations, {} inactive simulations".format(
                 np.count_nonzero(
diff --git a/micro_manager/adaptivity/local_adaptivity.py b/micro_manager/adaptivity/local_adaptivity.py
index cd465a0b..3fc45c2a 100644
--- a/micro_manager/adaptivity/local_adaptivity.py
+++ b/micro_manager/adaptivity/local_adaptivity.py
@@ -28,7 +28,7 @@ def compute_adaptivity(
             similarity_dists_nm1: np.ndarray,
             is_sim_active_nm1: np.ndarray,
             sim_is_associated_to_nm1: np.ndarray,
-            data_for_adaptivity: dict):
+            data_for_adaptivity: dict) -> tuple:
         """
         Compute adaptivity locally (within a rank).
 
@@ -55,6 +55,12 @@ def compute_adaptivity(
         is_sim_active : numpy array
             1D array, True is sim is active, False if sim is inactive.
         """
+        for name in data_for_adaptivity.keys():
+            if name not in self._adaptivity_data_names:
+                raise ValueError(
+                    "Data for adaptivity must be one of the following: {}".format(
+                        self._adaptivity_data_names.keys()))
+
         similarity_dists = self._get_similarity_dists(dt, similarity_dists_nm1, data_for_adaptivity)
 
         # Operation done globally if global adaptivity is chosen
diff --git a/tests/unit/test_adaptivity_parallel.py b/tests/unit/test_adaptivity_parallel.py
index 2f1b2a4e..189c45cf 100644
--- a/tests/unit/test_adaptivity_parallel.py
+++ b/tests/unit/test_adaptivity_parallel.py
@@ -105,7 +105,7 @@ def test_update_all_active_sims_global_adaptivity(self):
             rank=self._rank,
             comm=self._comm)
 
-        adaptivity_controller._adaptivity_data_names = {"data1": "scalar", "data2": "scalar"}
+        adaptivity_controller._adaptivity_data_names = {"data1": "scalar", "data2": "scalar", "data3": "vector"}
 
         class MicroSimulation():
             def __init__(self, global_id) -> None: