added score_answer implementation and tests

reasoning_gym/algebra/intermediate_integration.py

@@ -1,6 +1,6 @@
 import random
 from dataclasses import dataclass
-from typing import Optional
+from typing import Any, Dict, Optional
 
 import sympy
 
@@ -221,16 +221,43 @@ class IntermediateIntegrationDataset(ProceduralDataset):
                 integrand = self._generate_repeated_parts(rng, x)
 
         answer = sympy.integrate(integrand, x)
+        answer_str = str(answer) + " + C"
+
         return {
             "question": rng.choice(self.prompt_template).format(integrand=integrand),
-            "answer": str(answer) + " + C",
+            "answer": answer_str,
             "metadata": {
                 "integrand": str(integrand),
                 "problem_type": problem_type,
                 "variable": str(x),
                 "type": substitution_type if problem_type == "substitution" else parts_type,
+                "expected_answer_expression": answer,
             },
         }
 
+    def score_answer(self, answer: Optional[str], metadata: Dict[str, Any]) -> float:
+        """Determine if the solution provided solves the problem"""
+        reward = 0.0
+        if answer is not None:
+            try:
+                var = metadata["variable"]
+                x = sympy.Symbol(var)
+                # Parse answer while allowing integration constant 'C'
+                user_expr = sympy.parse_expr(answer, local_dict={var: x, "C": sympy.Symbol("C")})
+                # Compute derivative of student's answer
+                derivative = sympy.diff(user_expr, x)
+                integrand = sympy.parse_expr(metadata["integrand"], local_dict={var: x})
+
+                # Check mathematical equivalence through simplification
+                if sympy.simplify(derivative - integrand) == 0:
+                    reward = 1.0
+                elif answer.strip():
+                    reward = 0.05
+                else:
+                    reward = 0.01
+            except:
+                reward = 0.01
+        return reward
+
 
 register_dataset("intermediate_integration", IntermediateIntegrationDataset, IntermediateIntegrationConfig)