From 34d3aad25d85e3c2c4e0b0e1991432ab04524fab Mon Sep 17 00:00:00 2001
From: ellabarkan <ella@il.ibm.com>
Date: Sun, 11 Aug 2024 09:00:44 -0400
Subject: [PATCH 1/2] added fix for tupples

---
 fuse/eval/metrics/metrics_common.py | 29 +++++++++++++++++++++++++++--
 1 file changed, 27 insertions(+), 2 deletions(-)

diff --git a/fuse/eval/metrics/metrics_common.py b/fuse/eval/metrics/metrics_common.py
index 464503ab5..99c37aa49 100644
--- a/fuse/eval/metrics/metrics_common.py
+++ b/fuse/eval/metrics/metrics_common.py
@@ -887,6 +887,23 @@ def reset(self) -> None:
         self._metric.reset()
         return super().reset()
 
+    @staticmethod
+    def _convert_tuples(ids: List[Tuple[str, int]]) -> np.ndarray:
+
+        sample_tuple = ids[0]
+        dtype_tuple = []
+
+        for i, tuple_elem in enumerate(sample_tuple):
+            if isinstance(tuple_elem, str):
+                max_len = max(len(str(el[i])) for el in ids)
+                dtype_tuple.append((f"field{i}", f"U{max_len}"))
+            else:
+                dtype_tuple.append((f"field{i}", type(tuple_elem)))
+
+        ids = np.array(ids, dtype=dtype_tuple)
+        ids = [tuple(x) for x in ids]
+        return ids
+
     def eval(
         self, results: Dict[str, Any] = None, ids: Optional[Sequence[Hashable]] = None
     ) -> Dict[str, Any]:
@@ -902,7 +919,11 @@ def eval(
             raise Exception(
                 "Error: confidence interval is supported only when a unique identifier is specified. Add key 'id' to your data"
             )
-        ids = np.array(ids)
+
+        if isinstance(ids[0], tuple):
+            ids = self._convert_tuples(ids)
+        else:
+            ids = np.array(ids)
 
         rnd = np.random.RandomState(self._rnd_seed)
         original_sample_results = self._metric.eval(results, ids=ids)
@@ -920,7 +941,11 @@ def eval(
                 stratum_filter = stratum_id == stratum
                 n_stratum = sum(stratum_filter)
                 random_sample = rnd.randint(0, n_stratum, size=n_stratum)
-                sampled_ids[stratum_filter] = ids[stratum_filter][random_sample]
+
+                flt_indx = np.where(stratum_filter)[0]
+                for i, idx in enumerate(random_sample):
+                    sampled_ids[flt_indx[i]] = ids[flt_indx[idx]]
+
             boot_results.append(self._metric.eval(results, sampled_ids))
 
         # results can be either a list of floats or a list of dictionaries

From f54914081f7cca14b330235d9cfafbbdb7f1972a Mon Sep 17 00:00:00 2001
From: ellabarkan <ella@il.ibm.com>
Date: Mon, 19 Aug 2024 08:18:02 -0400
Subject: [PATCH 2/2] fixed the signature of tupple convert method

---
 fuse/eval/metrics/metrics_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/fuse/eval/metrics/metrics_common.py b/fuse/eval/metrics/metrics_common.py
index 99c37aa49..fbd98a287 100644
--- a/fuse/eval/metrics/metrics_common.py
+++ b/fuse/eval/metrics/metrics_common.py
@@ -888,7 +888,7 @@ def reset(self) -> None:
         return super().reset()
 
     @staticmethod
-    def _convert_tuples(ids: List[Tuple[str, int]]) -> np.ndarray:
+    def _convert_tuples(ids: List[Tuple[Any, ...]]) -> np.ndarray:
 
         sample_tuple = ids[0]
         dtype_tuple = []