Fix bug with original optimum using (#181)

* fix bug with original optimum using

* add var for number of constraints and fix objective function value

---------

Co-authored-by: Marina Usova <usova@itmm.unn.com>

iOpt/output_system/listeners/static_painters.py

@@ -40,8 +40,10 @@ def __init__(self, file_name: str, path_for_saves="", mode='analysis', calc='obj
  self.search_dataSorted = []
  self.bestValueSorted = []
  self.number_of_parallel_points = 1
+ self.number_of_constraints = 0
 
  def before_method_start(self, method: Method):
+ self.number_of_constraints = method.task.problem.number_of_constraints
  if method.task.problem.number_of_float_variables > 2 and self.calc == 'interpolation':
  raise Exception(
  "StaticDiscreteListener with calc 'interpolation' supported with dimension <= 2")
@@ -50,7 +52,7 @@ def before_method_start(self, method: Method):
  def on_end_iteration(self, new_points, solution: Solution):
  for newPoint in new_points:
  self.search_dataSorted.append(newPoint)
- self.bestValueSorted.append(solution.best_trials[0].function_values[0].value)
+ self.bestValueSorted.append(solution.best_trials[0].function_values[self.number_of_constraints].value)
 
  def on_method_stop(self, search_data: SearchData,
  solution: Solution, status: bool):
@@ -64,8 +66,8 @@ def on_method_stop(self, search_data: SearchData,
  solution.problem.lower_bound_of_float_variables,
  solution.problem.upper_bound_of_float_variables,
  self.file_name, self.path_for_saves, solution.problem.calculate,
- solution.best_trials[0].function_values[0].value,
- search_data, self.number_of_parallel_points)
+ solution.best_trials[0].function_values[self.number_of_constraints].value,
+ search_data, self.number_of_parallel_points, self.number_of_constraints)
  if self.mode == 'analysis':
  painter.paint_analisys(mrks=2)
  elif self.mode == 'bestcombination':
@@ -105,11 +107,15 @@ def __init__(self, file_name: str, path_for_saves="", indx=0, is_points_at_botto
  self.parameterInNDProblem = indx
  self.is_points_at_bottom = is_points_at_bottom
  self.mode = mode
+ self.number_of_constraints = 0
+
+ def before_method_start(self, method: Method):
+ self.number_of_constraints = method.task.problem.number_of_constraints
 
  def on_method_stop(self, search_data: SearchData,
  solution: Solution, status: bool):
  painter = StaticPainter(search_data, solution, self.mode, self.is_points_at_bottom,
- self.parameterInNDProblem, self.path_for_saves, self.file_name)
+ self.parameterInNDProblem, self.path_for_saves, self.file_name, self.number_of_constraints)
  painter.paint_objective_func()
  painter.paint_points()
  painter.paint_optimum()
@@ -149,11 +155,14 @@ def __init__(self, file_name: str, path_for_saves="", vars_indxs=[0, 1], mode='l
  self.parameters = vars_indxs
  self.mode = mode
  self.calc = calc
+ self.number_of_constraints = 0
+ def before_method_start(self, method: Method):
+ self.number_of_constraints = method.task.problem.number_of_constraints
 
  def on_method_stop(self, search_data: SearchData,
  solution: Solution, status: bool, ):
  painter = StaticPainterND(search_data, solution, self.parameters, self.mode, self.calc,
- self.file_name, self.path_for_saves)
+ self.file_name, self.path_for_saves, self.number_of_constraints)
  painter.paint_objective_func()
  painter.paint_points()
  painter.paint_optimum()

iOpt/output_system/outputers/console_outputer.py

@@ -13,6 +13,7 @@ def __init__(self, problem: Problem, parameters: SolverParameters):
  self.__functions = OutputFunctions()
  self.iterNum = 1
  self.ndv = self.problem.number_of_discrete_variables
+ self.number_of_constraints = self.problem.number_of_constraints
 
  def print_init_info(self):
  self.__functions.print_init(
@@ -57,7 +58,7 @@ def print_best_point_info(self, solution, iters):
  else:
  best_trial_point = solution.best_trials[0].point.float_variables
  best_trial_d_point = solution.best_trials[0].point.discrete_variables
- best_trial_value = solution.best_trials[0].function_values[self.problem.number_of_constraints].value
+ best_trial_value = solution.best_trials[0].function_values[self.number_of_constraints].value
  self.__functions.print_best(
  solution.number_of_global_trials,
  solution.number_of_local_trials,
@@ -72,7 +73,7 @@ def print_best_point_info(self, solution, iters):
  def print_final_result_info(self, solution: Solution, status: bool):
  best_trial_point = solution.best_trials[0].point.float_variables
  best_trial_d_point = solution.best_trials[0].point.discrete_variables
- best_trial_value = solution.best_trials[0].function_values[self.problem.number_of_constraints].value
+ best_trial_value = solution.best_trials[0].function_values[self.number_of_constraints].value
  self.__functions.print_result(
  status,
  solution.number_of_global_trials,

iOpt/output_system/painters/animate_painters.py

@@ -16,12 +16,14 @@ def __init__(self, is_points_at_bottom, parameter_in_nd_problem, path_for_saves,
  self.objFunc = None
  self.parameterInNDProblem = parameter_in_nd_problem
  self.section = []
+ self.number_of_constraints = 0
 
  # настройки графика
  self.plotter = AnimatePlotter2D(parameter_in_nd_problem, 0, 1)
 
  def set_problem(self, problem: Problem):
  self.objFunc = problem.calculate
+ self.number_of_constraints = self.problem.number_of_constraints
 
  for i in range(problem.number_of_float_variables):
  self.section.append(float(problem.upper_bound_of_float_variables[i]) - float(problem.lower_bound_of_float_variables[i]))
@@ -44,7 +46,7 @@ def paint_points(self, curr_points):
 
  def paint_optimum(self, solution: Solution):
  optimum = solution.best_trials[0].point.float_variables[self.parameterInNDProblem]
- optimumVal = solution.best_trials[0].function_values[0].value
+ optimumVal = solution.best_trials[0].function_values[self.number_of_constraints].value
 
  value = optimumVal
 
@@ -79,6 +81,7 @@ def __init__(self, parameters_in_nd_problem, path_for_saves, file_name):
  self.objFunc = None
  self.parametersInNDProblem = parameters_in_nd_problem
  self.section = []
+ self.number_of_constraints = 0
 
  # настройки графика
  self.plotter = AnimatePlotter3D(parameters_in_nd_problem)
@@ -103,7 +106,7 @@ def paint_points(self, curr_points):
  def paint_optimum(self, solution: Solution):
  optimum = [solution.best_trials[0].point.float_variables[self.parametersInNDProblem[0]],
  solution.best_trials[0].point.float_variables[self.parametersInNDProblem[1]]]
- optimumVal = solution.best_trials[0].function_values[0].value
+ optimumVal = solution.best_trials[0].function_values[self.number_of_constraints].value
 
  self.plotter.plot_points(optimum, [], 'red', 'o', 4)
 

iOpt/output_system/painters/plotters/plotters.py

@@ -303,12 +303,14 @@ def plot_by_grid(self, calculate, section, points_count=100):
  xv, yv = np.meshgrid(x1, x2)
  z = []
 
+ fv = section.copy()
+
  for i in range(points_count):
  z_ = []
  for j in range(points_count):
- section[self.indexes[0]] = xv[i, j]
- section[self.indexes[1]] = yv[i, j]
- z_.append(calculate(section))
+ fv[self.indexes[0]] = xv[i, j]
+ fv[self.indexes[1]] = yv[i, j]
+ z_.append(calculate(fv))
  z.append(z_)
 
  self.ax.contour(x1, x2, z, linewidths=1, levels=25, cmap=plt.cm.viridis)

iOpt/output_system/painters/static_painters.py

@@ -12,14 +12,15 @@
 class DiscretePainter(Painter):
  def __init__(self, search_data_sorted, bestsvalues, pcount, floatdim, optimumPoint, discreteValues,
  discrete_name, mode, calc, subparameters, lb, rb, file_name, path_for_saves, calculate,
- optimum_value, search_data, number_of_parallel_points):
+ optimum_value, search_data, number_of_parallel_points, number_of_constraints):
  self.path_for_saves = path_for_saves
  self.file_name = file_name
  self.calc = calc
  self.calculate = calculate
  self.optimum = optimumPoint
  self.optimumVal = optimum_value
  self.number_of_parallel_points = number_of_parallel_points
+ self.number_of_constraints = number_of_constraints
 
  self.values = []
  self.points = []
@@ -130,7 +131,8 @@ def __init__(self, search_data: SearchData,
  is_points_at_bottom,
  parameter_in_nd_problem,
  path_for_saves,
- file_name
+ file_name,
+ number_of_constraints
  ):
  self.path_for_saves = path_for_saves
  self.file_name = file_name
@@ -139,6 +141,7 @@ def __init__(self, search_data: SearchData,
  self.is_points_at_bottom = is_points_at_bottom
 
  self.objFunc = solution.problem.calculate
+ self.number_of_constraints = number_of_constraints
 
  # формируем массив точек итераций для графика
  self.points = []
@@ -153,7 +156,7 @@ def __init__(self, search_data: SearchData,
 
  self.optimum = solution.best_trials[0].point.float_variables
  self.optimumC = solution.best_trials[0].point.float_variables[parameter_in_nd_problem]
- self.optimumValue = solution.best_trials[0].function_values[0].value
+ self.optimumValue = solution.best_trials[0].function_values[self.number_of_constraints].value
 
  # настройки графика
  self.plotter = Plotter2D(parameter_in_nd_problem,
@@ -202,14 +205,15 @@ def calculate_func(self, x):
  return fv.value
 
 class StaticPainterND(Painter):
- def __init__(self, search_data, solution, parameters, mode, calc, file_name, path_for_saves):
+ def __init__(self, search_data, solution, parameters, mode, calc, file_name, path_for_saves, number_of_constraints):
  self.path_for_saves = path_for_saves
  self.file_name = file_name
 
  self.objectFunctionPainterType = mode
  self.objectFunctionCalculatorType = calc
 
  self.objFunc = solution.problem.calculate
+ self.number_of_constraints = number_of_constraints
 
  # формируем массив точек итераций для графика
  self.points = []
@@ -223,7 +227,10 @@ def __init__(self, search_data, solution, parameters, mode, calc, file_name, pat
  self.values = self.values[1:-1]
 
  self.optimum = solution.best_trials[0].point.float_variables
- self.optimumValue = solution.best_trials[0].function_values[0].value
+ self.optimum_section = [solution.best_trials[0].point.float_variables[parameters[0]],
+ solution.best_trials[0].point.float_variables[parameters[1]]]
+
+ self.optimumValue = solution.best_trials[0].function_values[self.number_of_constraints].value
 
  self.leftBounds = [float(solution.problem.lower_bound_of_float_variables[parameters[0]]),
  float(solution.problem.lower_bound_of_float_variables[parameters[1]])]
@@ -258,7 +265,7 @@ def paint_points(self, curr_point: SearchDataItem = None):
  self.plotter.plot_points(self.points, self.values, 'blue', 'o', 4)
 
  def paint_optimum(self, solution: Solution = None):
- self.plotter.plot_points([self.optimum], [self.optimumValue], 'red', 'o', 4)
+ self.plotter.plot_points([self.optimum_section], [self.optimumValue], 'red', 'o', 4)
 
  def save_image(self):
  if not os.path.isdir(self.path_for_saves):