* Now possible to indicate in the Init if a subsystem has variation, #33

pyDMPC/ControlFramework/Init_Geo.py

@@ -122,6 +122,7 @@
 IDs_inputs = []
 T_set = []
 Q_set = []
+variation = []
 
 """ Subsystems """
 # Ground
@@ -140,6 +141,7 @@
 cost_par.append("decisionVariables.y[1]")
 T_set.append(285)
 Q_set.append(2200)
+variation.append(True)
 
 
 # Building
@@ -158,3 +160,4 @@
 cost_par.append("decisionVariables.y[1]")
 T_set.append(295)
 Q_set.append(0)
+variation.append(True)

pyDMPC/ControlFramework/Subsystem.py

@@ -19,7 +19,7 @@ def __init__(self, name, position,
  bounds_DVs,model_path, names_BCs,
  num_VarsOut, names_DVs,
  output_vars, initial_names, IDs_initial_values,IDs_inputs,cost_par,
- T_set,Q_set, type_subSyst=None):
+ T_set,Q_set,variation, type_subSyst=None):
  self._name = name
  self._type_subSyst = type_subSyst
  self._num_DVs = num_DVs
@@ -41,6 +41,7 @@ def __init__(self, name, position,
  self._IDs_inputs = IDs_inputs
  self.T_set = T_set
  self.Q_set = Q_set
+ self.variation = variation
 
 
  def GetNeighbour(self, neighbour_name):
@@ -110,7 +111,10 @@ def CalcDVvalues(self, time_step, time_storage, iter, model):
  if time_step-time_storage < Init.optimization_interval and time_step != Init.sync_rate:
  # Interpolation
  try:
- [commands, costs, outputs] = BExMoC.Interpolation(self.measurements, self.lookUpTables[1], self._bounds_DVs, self.lookUpTables[0], self.lookUpTables[2])
+ [commands, costs, outputs] = BExMoC.Interpolation(
+ self.measurements, self.lookUpTables[1], 
+ self._bounds_DVs, self.lookUpTables[0], 
+ self.lookUpTables[2],self.variation)
 
  except:
  commands = []
@@ -135,7 +139,10 @@ def CalcDVvalues(self, time_step, time_storage, iter, model):
  sio.savemat((Init.path_res +'\\'+Init.name_wkdir + '\\' + self._name + '\\' + 'OptimizerTrack.mat' ), {'OptimizerTrackCounter11': res_grid})
 
  try:
- [commands, costs, outputs] = BExMoC.Interpolation(self.measurements, self.lookUpTables[1], self._bounds_DVs, self.lookUpTables[0], self.lookUpTables[2])
+ [commands, costs, outputs] = BExMoC.Interpolation(
+ self.measurements, self.lookUpTables[1], 
+ self._bounds_DVs, self.lookUpTables[0], 
+ self.lookUpTables[2], self.variation)
 
  print('measurements: ' + str(self.measurements))
  print('commands: ' +str(commands))

pyDMPC/ControlFramework/System.py

@@ -53,6 +53,7 @@ def GenerateSubSys(self):
  Init.cost_par[i],
  Init.T_set[i],
  Init.Q_set[i],
+ Init.variation[i],
  Init.type_subSyst[i])
  )
  subsystems.sort(key = lambda x: x.position)

pyDMPC/ControlFramework/algorithm/BExMoC.py

@@ -191,7 +191,8 @@ def CalcLookUpTables(s, time_storage, init_conds):
  return [storage_cost, storage_DV, storage_out, exDestArr, storage_grid]
 
 
-def Interpolation(measurements_SubSys, storage_DV, bounds_DVs, storage_cost, storage_out):
+def Interpolation(measurements_SubSys, storage_DV, bounds_DVs, storage_cost, 
+ storage_out, variation):
  """
  Interpolate the values of the decision variables, costs and outputs
 
@@ -211,57 +212,69 @@ def Interpolation(measurements_SubSys, storage_DV, bounds_DVs, storage_cost, sto
  Reformat the boundary conditions, decision variables, outputs and
  costs
  """
- cond_BC = [True if L<len(measurements_SubSys) else False for L in range(len(storage_DV[0]))]
- cond_DV = [False if L<len(measurements_SubSys) else True for L in range(len(storage_DV[0]))]
- cond_Out = [False if L<len(measurements_SubSys) else True for L in range(len(storage_out[0]))]
- cond_Costs = cond_DV
-
- grid_points = np.compress(cond_BC,storage_DV, axis = 1)
- grid_point_values = np.compress(cond_DV,storage_DV, axis = 1)
- grid_measurements = measurements_SubSys[::-1]
- grid_point_values_costs = np.compress(cond_Costs,storage_cost, axis = 1)
- grid_point_values_out = np.compress(cond_Out,storage_out, axis = 1)
-
- print("Grid points:")
- print(grid_points)
- print("values:")
- print(grid_point_values)
- print("measurements:")
- print(grid_measurements)
-
- """ Interpolation of reformatted data """
- try:
- commands = interpolate.griddata(grid_points, grid_point_values,grid_measurements ,method='linear')
- costs = interpolate.griddata(grid_points, grid_point_values_costs,grid_measurements ,method='linear')
- out = interpolate.griddata(grid_points, grid_point_values_out, grid_measurements ,method='linear')
-
- print("commands: " + str(commands))
- print("costs: " + str(costs))
- print("outputs: " + str(out))
-
- # Check if commands are in range, else set to boundary values
- for i, val in enumerate(commands):
- if val < bounds_DVs[i]:
- commands[i] = bounds_DVs[i]
- print('Val < lower Bound')
- elif val > bounds_DVs[i+1]:
- commands[i] = bounds_DVs[i+1]
- print('Val > higher Bound')
- elif val >= bounds_DVs[i] and val <= bounds_DVs[i+1]:
- commands[i] = val
- # last case: invalid interpolation
- else:
- commands[i] = bounds_DVs[i]
- print('interpolation failed!')
- return [commands, costs, out]
-
- except:
+ if variation: 
+ cond_BC = [True if L<len(measurements_SubSys) else False for L in range(len(storage_DV[0]))]
+ cond_DV = [False if L<len(measurements_SubSys) else True for L in range(len(storage_DV[0]))]
+ cond_Out = [False if L<len(measurements_SubSys) else True for L in range(len(storage_out[0]))]
+ cond_Costs = cond_DV
+
+ grid_points = np.compress(cond_BC,storage_DV, axis = 1)
+ grid_point_values = np.compress(cond_DV,storage_DV, axis = 1)
+ grid_measurements = measurements_SubSys[::-1]
+ grid_point_values_costs = np.compress(cond_Costs,storage_cost, axis = 1)
+ grid_point_values_out = np.compress(cond_Out,storage_out, axis = 1)
+
+ print("Grid points:")
+ print(grid_points)
+ print("values:")
+ print(grid_point_values)
+ print("measurements:")
+ print(grid_measurements)
+
+ """ Interpolation of reformatted data """
+ try:
+ commands = interpolate.griddata(grid_points, grid_point_values,grid_measurements ,method='linear')
+ costs = interpolate.griddata(grid_points, grid_point_values_costs,grid_measurements ,method='linear')
+ out = interpolate.griddata(grid_points, grid_point_values_out, grid_measurements ,method='linear')
+
+ print("commands: " + str(commands))
+ print("costs: " + str(costs))
+ print("outputs: " + str(out))
+
+ # Check if commands are in range, else set to boundary values
+ for i, val in enumerate(commands):
+ if val < bounds_DVs[i]:
+ commands[i] = bounds_DVs[i]
+ print('Val < lower Bound')
+ elif val > bounds_DVs[i+1]:
+ commands[i] = bounds_DVs[i+1]
+ print('Val > higher Bound')
+ elif val >= bounds_DVs[i] and val <= bounds_DVs[i+1]:
+ commands[i] = val
+ # last case: invalid interpolation
+ else:
+ commands[i] = bounds_DVs[i]
+ print('interpolation failed!')
+
+ except:
+ commands = []
+ costs = []
+ out = []
+
+ for i in range(0,len(storage_DV)):
+ commands.append(storage_DV[0,0])
+ costs.append(0)
+ out.append(0)
+ print('interpolation failed!')
+
+ else:
  commands = []
  costs = []
  out = []
-
+ 
  for i in range(0,len(storage_DV)):
- commands.append(storage_DV[0,0])
- costs.append(0)
- out.append(0)
- print('interpolation failed!')
+ commands.append(storage_DV[0,2])
+ costs.append(storage_cost[0,2])
+ out.append(storage_out[0,2])
+
+ return [commands, costs, out]