Add method for evaluating decision rules through interface

Author: shermanjasonaf

pyomo/contrib/pyros/dr_interface.py

@@ -232,6 +232,44 @@ def get_num_coeffs_per_ss_dim(self, simplified=True):
         else:
             return sum(num_uncertain_params**order for order in range(self.order + 1))
 
+    def evaluate(self, uncertain_param_values, ss_idxs=None):
+        """
+        Evaluate decision rule at a given uncertain
+        parameter realization.
+
+        Parameters
+        ----------
+        uncertain_param_values : (N,) array-like
+            Uncertain parameter realization.
+        ss_idxs : None or list of int, optional
+            Second-stage variable space dimensions for which
+            to perform the evaluations. If `None` is passed,
+            then evaluation is performed for all dimensions.
+
+        Returns
+        -------
+        numpy.ndarray
+            Array, of length ``len(ss_idxs)``, containing the
+            polynomial evaluation for each of the specified
+            second-stage variable space dimensions.
+        """
+        if ss_idxs is None:
+            ss_idxs = list(range(self.second_stage_var_dim))
+        param_val_arr = np.asarray(uncertain_param_values)
+        static_vals = self.static_coeffs[ss_idxs]
+
+        affine_vals = 0
+        if self.order >= 1:
+            affine_vals = self.affine_coeffs[ss_idxs] @ param_val_arr
+
+        quadratic_vals = 0
+        if self.order >= 2:
+            quadratic_vals = (
+                param_val_arr @ self.quadratic_coeffs[ss_idxs] @ param_val_arr
+            )
+
+        return static_vals + affine_vals + quadratic_vals
+
     def get_param_idx_to_coeff_map(self, ss_idx, simplified=True):
         """
         Cast the coefficients contained in `self` to a map

pyomo/contrib/pyros/tests/test_dr_interface.py

@@ -782,5 +782,28 @@ def test_generate_dr_equations(self):
         )
 
 
+class TestEvaluateDR(unittest.TestCase):
+    @parameterized.parameterized.expand([[0], [1], [2]])
+    def test_evaluate_dr(self, dr_order):
+        static_coeffs = [0.5, 0.8]
+        affine_coeffs = [[2, 4, 6], [8, 9, 10]]
+        quadratic_coeffs = [
+            [[0.01, 0.02, 0.03], [0.04, 0.05, 0.06], [0.07, 0.08, 0.09]],
+            [[0.10, 0.11, 0.12], [0.13, 0.14, 0.15], [0.16, 0.17, 0.18]],
+        ]
+        dri = DecisionRuleInterface(
+            static_coeffs=static_coeffs,
+            affine_coeffs=affine_coeffs if dr_order >= 1 else None,
+            quadratic_coeffs=quadratic_coeffs if dr_order >= 2 else None,
+        )
+        dr_eval = dri.evaluate([2, 1, 0.5])
+        expected_evals = {
+            0: static_coeffs,
+            1: static_coeffs + np.array([11, 30]),
+            2: static_coeffs + np.array([11, 30]) + np.array([0.4025, 1.505]),
+        }
+        np.testing.assert_allclose(dr_eval, expected_evals[dr_order])
+
+
 if __name__ == "__main__":
     unittest.main()