extract_results uses resample_into

optimization_model.py

@@ -22,7 +22,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 THE SOFTWARE.
 """
 
-from Model_Library.dynamics import Profile
+from Model_Library.dynamics import Profile, resample_into
 
 from enum import Enum
 import numpy as np
@@ -150,10 +150,13 @@ class EntityResult:
                 self.var_kinds[var_name] = ('i_prime_result', n_i_prime_vars)
                 n_i_prime_vars += 1
                 
+        self.n_u_vars = n_u_vars
         self.u_result = np.empty(n_u_vars, dtype=float)
 
+        self.n_i_vars = n_i_vars
         self.i_result = np.empty((n_i_vars, dynamic.shape()), dtype=float)
 
+        self.n_i_prime_vars = n_i_prime_vars
         self.i_prime_result = np.empty((n_i_prime_vars, dynamic.state_shape()), dtype=float)
 
         self.dynamic = dynamic
@@ -161,17 +164,23 @@ class EntityResult:
         self.sub_results = dict()
 
     def extract_result(self, block):
-        if self.dynamic != block.dynamic:
-            raise ValueError('Cannot extract results from a block into a EntitResult with a different dynamic!')
+        # TODO: when the resampling is simple copying, then detect that here and extract in the loop over self.var_kinds the values directly into the EntityResult instead of creating new ndarrays
+        u_values = np.empty(self.n_u_vars, dtype=float)
+        i_values = np.empty((self.n_i_vars, block.dynamic.shape()), dtype=float)
+        i_prime_values = np.empty((self.n_i_prime_vars, block.dynamic.state_shape()), dtype=float)
         for var_name, (var_kind, index) in self.var_kinds.items():
             if var_kind == 'i_result':
-                values = block.component_dict[var_name].get_values()
-                self.i_result[index] = np.fromiter((values[t] for t in block.T), float)
+                value_object = block.component_dict[var_name].get_values()
+                i_values[index] = np.fromiter((value_object[t] for t in block.T), float)
             elif var_kind == 'u_result':
-                self.u_result[index] = pyo.value(block.component_dict[var_name])
+                u_values[index] = pyo.value(block.component_dict[var_name])
             elif var_kind == 'i_prime_result':
-                values = block.component_dict[var_name].get_values()
-                self.i_prime_result[index] = np.fromiter((values[t] for t in block.T_prime), float)
+                value_object = block.component_dict[var_name].get_values()
+                i_prime_values[index] = np.fromiter((value_object[t] for t in block.T_prime), float)
+
+        self.u_result = u_values
+        resample_into(i_values, block.dynamic, self.i_result, self.dynamic)
+        resample_into(i_prime_values, block.dynamic, self.i_prime_result, self.dynamic)
 
     def add_sub_result(self, key, result):
         self.sub_results[key] = result