Add common function to both adaptivity variants for general micro out…

…put field

micro_manager/adaptivity/global_adaptivity.py

@@ -83,14 +83,20 @@ def compute_adaptivity(
         micro_sims : list
             List of objects of class MicroProblem, which are the micro simulations
         adaptivity_data_nm1 : list
-            List of numpy arrays: similarity_dists (2D array having similarity distances between each micro simulation pair), is_sim_active (1D array having state (active or inactive) of each micro simulation), sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
+            List of numpy arrays:
+                similarity_dists (2D array having similarity distances between each micro simulation pair)
+                is_sim_active (1D array having state (active or inactive) of each micro simulation)
+                sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
         data_for_adaptivity : dict
             Dictionary with keys as names of data to be used in the similarity calculation, and values as the respective data for the micro simulations
 
         Results
         -------
         list
-            List of numpy arrays: similarity_dists (2D array having similarity distances between each micro simulation pair), is_sim_active (1D array having state (active or inactive) of each micro simulation), sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
+            List of numpy arrays:
+                similarity_dists (2D array having similarity distances between each micro simulation pair)
+                is_sim_active (1D array having state (active or inactive) of each micro simulation)
+                sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
         """
         for name in data_for_adaptivity.keys():
             if name not in self._adaptivity_data_names:
@@ -142,7 +148,55 @@ def compute_adaptivity(
 
         return [similarity_dists, is_sim_active, sim_is_associated_to]
 
-    def communicate_micro_output(
+    def get_active_sim_ids(self) -> np.ndarray:
+        """
+        Get the ids of active simulations.
+
+        Returns
+        -------
+        numpy array
+            1D array of active simulation ids
+        """
+        return self._active_sim_ids
+
+    def get_inactive_sim_ids(self) -> np.ndarray:
+        """
+        Get the ids of inactive simulations.
+
+        Returns
+        -------
+        numpy array
+            1D array of inactive simulation ids
+        """
+        return self._inactive_sim_ids
+
+    def get_full_field_micro_output(
+        self, adaptivity_data: list, micro_output: list
+    ) -> list:
+        """
+        Get the full field micro output from active simulations to inactive simulations.
+
+        Parameters
+        ----------
+        adaptivity_data : list
+            List of numpy arrays:
+                similarity_dists (2D array having similarity distances between each micro simulation pair)
+                is_sim_active (1D array having state (active or inactive) of each micro simulation)
+                sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
+        micro_output : list
+            List of dicts having individual output of each simulation. Only the active simulation outputs are entered.
+
+        Returns
+        -------
+        micro_output : list
+            List of dicts having individual output of each simulation. Active and inactive simulation outputs are entered.
+        """
+        micro_sims_output = deepcopy(micro_output)
+        self._communicate_micro_output(adaptivity_data[1:3], micro_sims_output)
+
+        return micro_sims_output
+
+    def _communicate_micro_output(
         self,
         adaptivity_data: list,
         micro_output: list,
@@ -201,28 +255,6 @@ def communicate_micro_output(
             for local_id in active_to_inactive_map[assoc_active_ids[count]]:
                 micro_output[local_id] = deepcopy(output)
 
-    def get_active_sim_ids(self) -> np.ndarray:
-        """
-        Get the ids of active simulations.
-
-        Returns
-        -------
-        numpy array
-            1D array of active simulation ids
-        """
-        return self._active_sim_ids
-
-    def get_inactive_sim_ids(self) -> np.ndarray:
-        """
-        Get the ids of inactive simulations.
-
-        Returns
-        -------
-        numpy array
-            1D array of inactive simulation ids
-        """
-        return self._inactive_sim_ids
-
     def _update_inactive_sims(
         self,
         similarity_dists: np.ndarray,

micro_manager/adaptivity/local_adaptivity.py

@@ -4,6 +4,7 @@
 each other. A global comparison is not done.
 """
 import numpy as np
+from copy import deepcopy
 
 from .adaptivity import AdaptivityCalculator
 
@@ -108,6 +109,37 @@ def get_inactive_sim_ids(self) -> np.ndarray:
         """
         return self._inactive_sim_ids
 
+    def get_full_field_micro_output(
+        self, adaptivity_data: list, micro_output: list
+    ) -> list:
+        """
+        Get the full field micro output from active simulations to inactive simulations.
+
+        Parameters
+        ----------
+        adaptivity_data : list
+            List of numpy arrays:
+                is_sim_active (1D array having state (active or inactive) of each micro simulation)
+                sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
+        micro_output : list
+            List of dicts having individual output of each simulation. Only the active simulation outputs are entered.
+
+        Returns
+        -------
+        micro_output : list
+            List of dicts having individual output of each simulation. Active and inactive simulation outputs are entered.
+        """
+        micro_sims_output = deepcopy(micro_output)
+
+        sim_is_associated_to = adaptivity_data[2]
+
+        for inactive_id in self._inactive_sim_ids:
+            micro_sims_output[inactive_id] = deepcopy(
+                micro_sims_output[sim_is_associated_to[inactive_id]]
+            )
+
+        return micro_sims_output
+
     def _update_inactive_sims(
         self,
         similarity_dists: np.ndarray,

micro_manager/micro_manager.py

@@ -126,7 +126,10 @@ def solve(self) -> None:
 
         dt = min(self._participant.get_max_time_step_size(), self._micro_dt)
 
-        # adaptivity_data is a of numpy arrays: similarity_dists (2D array having similarity distances between each micro simulation pair), is_sim_active (1D array having state (active or inactive) of each micro simulation), sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
+        # adaptivity_data is a list of numpy arrays:
+        # 1. similarity_dists (2D array having similarity distances between each micro simulation pair)
+        # 2. is_sim_active (1D array having state (active or inactive) of each micro simulation)
+        # 3. sim_is_associated_to (1D array with values of associated simulations of inactive simulations. Active simulations have None)
         adaptivity_data: list = []
 
         if self._is_adaptivity_on:
@@ -343,8 +346,6 @@ def initialize(self) -> None:
             self._global_ids_of_local_sims.append(sim_id)
             sim_id += 1
 
-        # self._micro_sims = [None] * self._local_number_of_sims  # DECLARATION
-
         # Setup for simulation crashes
         self._has_sim_crashed = [False] * self._local_number_of_sims
         if self._interpolate_crashed_sims:
@@ -706,13 +707,12 @@ def _solve_micro_simulations_with_adaptivity(
                 self._data_for_adaptivity,
             )
 
-            sim_is_associated_to = adaptivity_data[2]
-
             active_sim_ids = self._adaptivity_controller.get_active_sim_ids()
 
             for active_id in active_sim_ids:
                 self._micro_sims_active_steps[active_id] += 1
 
+        active_sim_ids = self._adaptivity_controller.get_active_sim_ids()
         inactive_sim_ids = self._adaptivity_controller.get_inactive_sim_ids()
 
         micro_sims_output = [None] * self._local_number_of_sims
@@ -779,16 +779,9 @@ def _solve_micro_simulations_with_adaptivity(
                     micro_sims_input, micro_sims_output, unset_sim, active_sim_ids
                 )
 
-        # For each inactive simulation, copy data from most similar active simulation
-        if self._adaptivity_type == "global":
-            self._adaptivity_controller.communicate_micro_output(
-                adaptivity_data[1:3], micro_sims_output
-            )
-        elif self._adaptivity_type == "local":
-            for inactive_id in inactive_sim_ids:
-                micro_sims_output[inactive_id] = deepcopy(
-                    micro_sims_output[sim_is_associated_to[inactive_id]]
-                )
+        self._adaptivity_controller.get_full_field_micro_output(
+            adaptivity_data, micro_sims_output
+        )
 
         # Resolve micro sim output data for inactive simulations
         for inactive_id in inactive_sim_ids: