new general map to map distance class

src/cryo_challenge/_map_to_map/map_to_map_distance_matrix.py

@@ -28,6 +28,34 @@ def vmap_distance(
     )(maps_gt)
 
 
+class MapToMapDistance:
+    def __init__(self, config):
+        self.config = config
+
+    def get_distance(self, map1, map2):
+        raise NotImplementedError()
+
+    def get_distance_matrix(self, maps1, maps2):
+        chunk_size_submission = self.config["analysis"]["chunk_size_submission"]
+        chunk_size_gt = self.config["analysis"]["chunk_size_gt"]
+        distance_matrix = torch.vmap(
+            lambda maps1: torch.vmap(
+                lambda maps2: self.get_distance(maps1, maps2),
+                chunk_size=chunk_size_submission,
+            )(maps2),
+            chunk_size=chunk_size_gt,
+        )(maps1)
+
+        return distance_matrix
+
+class L2Distance(MapToMapDistance):
+    def __init__(self, config):
+        super().__init__(config)
+
+    def get_distance(self, map1, map2):
+        return torch.norm(map1 - map2)**2
+
+
 def run(config):
     """
     Compare a submission to ground truth.
@@ -99,6 +127,13 @@ def run(config):
                 )
                 cost_matrix = cost_matrix.numpy()
                 computed_assets["fsc_matrix"] = fsc_matrix
+            elif cost_label == "nope":
+                l2_map2map_distance = L2Distance(config)
+                cost_matrix = l2_map2map_distance.get_distance_matrix(
+                    maps_gt_flat, maps_user_flat
+                ).numpy()
+                print('run new method')
+
             else:
                 cost_matrix = vmap_distance(
                     maps_gt_flat,
@@ -111,6 +146,7 @@ def run(config):
             cost_matrix_df = pd.DataFrame(
                 cost_matrix, columns=None, index=metadata_gt.populations.tolist()
             )
+            print(cost_matrix_df)
 
             # output results
             single_distance_results_dict = {