removed any hardcoded arguments

RunFile.py

@@ -45,17 +45,6 @@ print('Base directory:', base_dir)
 #-----------------------------------------------------------------------------
 
 args = parse_arguments()
-#args.model = 'anaesthesia_delivery'
-# args.drug_partition = [10,10,10]
-#args.bld_par_uncertainty = True
-#args.prism_java_memory = 32
-
-args.model = 'drone'
-args.drone_spring = True
-args.iterations = 1
-args.partition_plot = True
-args.drone_mc_iter = 20
-args.drone_mc_step = 1
 
 with open(os.path.join(base_dir, 'path_to_prism.txt')) as f:
     args.prism_folder = str(f.readlines()[0])

core/cvx_opt.py

@@ -53,12 +53,18 @@ class Controller(object):
         self.error_neg.value = error[:,0]
         self.error_pos.value = error[:,1]
         
-        self.prob.solve(warm_start = True, solver='ECOS')
-        
-        if self.prob.status == 'infeasible':
+        try:
+            self.prob.solve(warm_start = True, solver='ECOS')
+            
+            if self.prob.status == 'infeasible':
+                return False, None, None
+            else: 
+                return True, self.x_plus.value, self.u.value
+            
+        except:
+            # Throw an exception is CVXPY solver failed
+            print('-- Warning: Could not solve LP; skip this action')
             return False, None, None
-        else: 
-            return True, self.x_plus.value, self.u.value
         
         
         
@@ -91,18 +97,24 @@ class LP_vertices_contained(object):
         
         self.P_vertices.value = vertices
         
-        if self.solver == 'GUROBI':
-            self.prob.solve(warm_start = True, solver='GUROBI')
-        elif self.solver == 'ECOS':
-            self.prob.solve(warm_start = True, solver='ECOS')
-        elif self.solver == 'OSQP':
-            self.prob.solve(warm_start = True, solver='OSQP', eps_abs=1e-4, eps_rel=1e-4)
-        elif self.solver == 'SCS':
-            self.prob.solve(warm_start = True, solver='SCS')
-        else:
-            self.prob.solve(warm_start = True)
-        
-        if self.prob.status != "infeasible":
-            return True
-        else:
-            return False
\ No newline at end of file
+        try:
+            if self.solver == 'GUROBI':
+                self.prob.solve(warm_start = True, solver='GUROBI')
+            elif self.solver == 'ECOS':
+                self.prob.solve(warm_start = True, solver='ECOS')
+            elif self.solver == 'OSQP':
+                self.prob.solve(warm_start = True, solver='OSQP', eps_abs=1e-4, eps_rel=1e-4)
+            elif self.solver == 'SCS':
+                self.prob.solve(warm_start = True, solver='SCS')
+            else:
+                self.prob.solve(warm_start = True)
+                
+            if self.prob.status != "infeasible":
+                return True
+            else:
+                return False
+        except:
+            # Throw an exception is CVXPY solver failed
+            print('-- Warning: Could not solve LP; skip this state')
+            return False
+        
\ No newline at end of file

core/spec_definitions.py

@@ -188,8 +188,11 @@ class anaesthesia_delivery_spec(master.spec_master):
         width = self.partition['boundary'] @ np.array([-1, 1]) / self.partition['number']
         
         # Actions per dimension (if 'auto', equal to nr of regions)
-        self.targets['boundary']    = 'auto' #self.partition['boundary']
-        self.targets['number']      = 'auto' #self.partition['number']
+        self.targets['boundary']    = self.partition['boundary']
+        
+        self.targets['boundary'][:,0] = self.targets['boundary'][:,0] + width
+        self.targets['boundary'][:,1] = self.targets['boundary'][:,1] - width
+        self.targets['number']      = list(np.array(self.partition['number'])-2)
         
         self.goal = [
             np.array([[4, 6], [0, 10], [0, 10]])