Group observations by response (WIP)

src/ert/analysis/_es_update.py

@@ -295,21 +295,35 @@ def _get_obs_and_measure_data(
 
         df = filtered_response.to_dataframe().reset_index()
 
-        observation_keys.append(df["name"].to_list())
-        observation_values.append(df["observations"].to_list())
-        observation_errors.append(df["std"].to_list())
+        observation_keys.extend(
+            observation.to_dataframe()
+            .reset_index()["name"]
+            .to_numpy()
+            .reshape((len(filtered_response.name), -1))
+            .tolist()
+        )
+        observation_values.extend(
+            observation["observations"]
+            .to_dataframe()
+            .to_numpy()
+            .reshape((1, -1))
+            .tolist()
+        )
+        observation_errors.extend(
+            observation["std"].to_dataframe().to_numpy().reshape((1, -1)).tolist()
+        )
 
-        measured_data.append(
+        measured_data.extend(
             filtered_response["values"]
             .transpose(..., "realization")
-            .values.reshape((-1, len(filtered_response.realization)))
+            .values.reshape(
+                (len(filtered_response.name), -1, len(filtered_response.realization))
+            )
         )
     source_fs.load_responses.cache_clear()
 
-    # Measured_data, an array of 3 dimensions
-    # Outer dimension: One array per observation
-    # Mid dimension is ??? Sometimes length 1, sometimes nreals?
-    # Inner dimension: value is "values", index is realization
+    # Measured_data, an array of nd arrays with shape (1, nreals)
+    # Each inner array has 1 dimension containing obs key, and nreals "values"
     return (
         np.concatenate(measured_data, axis=0),
         np.concatenate(observation_values),