add objects

app/app_new_mcts.py

@@ -14,7 +14,7 @@
     rule_vocabulary = create_rules()
 
     init_graph = GraphGrammar()
-    env = SubStringDesignEnvironment(rule_vocabulary, evaluator_tendon_fast_debug,
+    env = SubStringDesignEnvironment(rule_vocabulary, evaluator_tendon_standart,
                                      mcts_hyper_default.max_number_rules, init_graph, 0)
 
     mcts = MCTS(env, mcts_hyper_default.C)

app/one_graph_simulation.py

@@ -1,19 +1,22 @@
-from mcts_run_setup import config_tendon
+import tendon_graph_evaluators
 
 from rostok.library.obj_grasp.objects import get_object_sphere
 from rostok.library.rule_sets.simple_designs import (
-    get_three_link_one_finger, get_three_link_one_finger_independent, get_two_link_three_finger, )
+    get_three_link_one_finger,
+    get_three_link_one_finger_independent,
+    get_two_link_three_finger,
+)
+if __name__ == "__main__":
+    # create blueprint for object to grasp
+    grasp_object_blueprint = get_object_sphere(0.05, mass=0.2)
 
-# create blueprint for object to grasp
-grasp_object_blueprint = get_object_sphere(0.05, mass=0.2)
+    control_optimizer = tendon_graph_evaluators.evaluator_tendon_standart_parallel
 
-# create reward counter using run setup function
-# control_optimizer = config_with_const_troques(grasp_object_blueprint)
-
-control_optimizer = config_tendon(grasp_object_blueprint)
-
-graph = get_three_link_one_finger_independent()
-graph = graph = get_two_link_three_finger() 
+    graph = get_three_link_one_finger_independent()
+    graph = graph = get_two_link_three_finger()
 
-rewsss = control_optimizer.calculate_reward(graph)
-pass
+    rewsss = control_optimizer.calculate_reward(graph)
+
+    first_object = control_optimizer.prepare_reward.reward_one_sim_scenario(
+        x=rewsss[1][0], graph=graph, sim=control_optimizer.simulation_scenario[0])
+    print(rewsss)