Repository: open-thought/reasoning-gym

Issue:
Fix pool_matrix `score_answer` method
The `pool_matrix` dataset contains an error in its `score_answer method`. Fix the dataset's score_answer implementation:

Answer 
```
7 8 5 7 5
1 6 0 3 8
7 1 5 7 8
```

Error:
 The DType <class 'numpy.dtypes.StrDType'> could not be promoted by <class 'numpy.dtypes._PyFloatDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtypes.StrDType'>, <class 'numpy.dtypes._PyFloatDType'>)


**Task**: handle the numpy data mismatch within `pool_matrix`'s  `score_answer` method

Hints from issue comments:

Solution patch:
diff --git a/reasoning_gym/algorithmic/pool_matrix.py b/reasoning_gym/algorithmic/pool_matrix.py
index 41b9117..002c0c0 100644
--- a/reasoning_gym/algorithmic/pool_matrix.py
+++ b/reasoning_gym/algorithmic/pool_matrix.py
@@ -102,8 +102,8 @@ class PoolMatrixDataset(ProceduralDataset):
 
         reward = 0.0
         try:
-            oracle_answer = np.array(entry["answer"])
-            answer = np.array(answer)
+            oracle_answer = np.loadtxt(entry["answer"].splitlines(), dtype=np.float32)
+            answer = np.loadtxt(answer.splitlines(), dtype=np.float32)
             if oracle_answer.shape == answer.shape and np.allclose(oracle_answer, answer):
                 reward = 1.0
             elif oracle_answer.shape == answer.shape:


Test patch:
diff --git a/tests/test_pool_matrix.py b/tests/test_pool_matrix.py
index aa3fe6b..c110967 100644
--- a/tests/test_pool_matrix.py
+++ b/tests/test_pool_matrix.py
@@ -136,3 +136,28 @@ def test_pool_matrix_answer():
         ]
     )
     assert np.allclose(dataset._average_pool(matrix, 2), np.array([[3.5, 5.5], [11.5, 13.5]]))
+
+
+def test_pool_matrix_score_answer():
+    config = PoolMatrixConfig(seed=42, size=100)
+    dataset = PoolMatrixDataset(config)
+    for entry in dataset:
+        assert dataset.score_answer(entry["answer"], entry=entry) == 1
+        assert 0.0 < dataset.score_answer("1 2.0\n3.0 4", entry=entry) <= 0.1
+        assert dataset.score_answer("one two three", entry=entry) == 0.0
+        assert dataset.score_answer("", entry=entry) == 0.0
+        assert dataset.score_answer(None, entry=entry) == 0.0
+
+
+def test_pool_matrix_int_answer():
+    config = PoolMatrixConfig(seed=42, size=10)
+    dataset = PoolMatrixDataset(config)
+    for entry in dataset:
+        matrix = np.loadtxt(entry["answer"].splitlines())
+        is_integer = np.equal(np.mod(matrix, 1), 0)
+        if is_integer.all():
+            matrix = matrix.astype(np.int32)
+            if matrix.ndim == 0:
+                matrix = matrix.reshape(1, 1)
+            int_answer = "\n".join(" ".join(str(x) for x in row) for row in matrix)
+            assert dataset.score_answer(answer=int_answer, entry=entry) == 1.0