From 8a8fe44a7cc4df33b4d6dcd74030c256ec142c12 Mon Sep 17 00:00:00 2001 From: LebedevIlyaG Date: Wed, 13 Sep 2023 08:24:21 +0300 Subject: [PATCH 1/2] Fixed a bug with running a local method on tasks with partially integer parameters (#162) --- iOpt/method/local_optimizer.py | 2 +- test/test_solving_test_problems.py | 17 ++++++++++++++++- 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/iOpt/method/local_optimizer.py b/iOpt/method/local_optimizer.py index 61508f8..ff75cf4 100644 --- a/iOpt/method/local_optimizer.py +++ b/iOpt/method/local_optimizer.py @@ -36,7 +36,7 @@ def evaluate_function(self, y: List[float]) -> float: if self.max_calcs != -1 and self.calcs_count >= self.max_calcs: function_value.value = sys.float_info.max return function_value.value - for i in range(self.task.problem.dimension): + for i in range(self.task.problem.number_of_float_variables): if (y[i] < self.task.problem.lower_bound_of_float_variables[i]) \ or (y[i] > self.task.problem.upper_bound_of_float_variables[i]): function_value.value = sys.float_info.max diff --git a/test/test_solving_test_problems.py b/test/test_solving_test_problems.py index bfe438c..b618c74 100644 --- a/test/test_solving_test_problems.py +++ b/test/test_solving_test_problems.py @@ -1,8 +1,10 @@ import unittest import numpy as np from iOpt.problem import Problem +from iOpt.trial import Point from problems.GKLS import GKLS from problems.rastrigin import Rastrigin +from problems.rastriginInt import RastriginInt from problems.xsquared import XSquared from problems.hill import Hill from problems.shekel import Shekel @@ -15,6 +17,7 @@ from iOpt.solver_parametrs import SolverParameters + class TestSolvingProblems(unittest.TestCase): """setUp method is overridden from the parent class Rastrigin""" @@ -29,7 +32,7 @@ def checkIsSolved(self, problem: Problem, params: SolverParameters, number_of_gl sol = solver.solve() # Проверяем что найденный АГП минимумом соответствуйте априори известному, для этой задачи, с точностью eps - for j in range(problem.dimension): + for j in range(problem.number_of_float_variables): fabsx = np.abs(problem.known_optimum[0].point.float_variables[j] - sol.best_trials[0].point.float_variables[j]) fm = params.eps * (problem.upper_bound_of_float_variables[j] - @@ -38,6 +41,7 @@ def checkIsSolved(self, problem: Problem, params: SolverParameters, number_of_gl # Проверяем что на решение потребовалось правильное число итераций АГП self.assertEqual(sol.number_of_global_trials, number_of_global_trials) + return sol def test_Rastrigin_Solve(self): r = 3.5 @@ -47,6 +51,17 @@ def test_Rastrigin_Solve(self): self.checkIsSolved(problem, params, number_of_global_trials) + def test_RastriginInt_Solve(self): + r = 3.5 + problem = RastriginInt(dimension=5, number_of_discrete_variables=3) + start_point: Point = Point(float_variables=[0.5, 0.5], discrete_variables=['A', 'B', 'A']) + params = SolverParameters(r=r, eps=self.epsVal, iters_limit=100000, start_point=start_point, + number_of_parallel_points=1, refine_solution=True) + number_of_global_trials = 5678 + + sol = self.checkIsSolved(problem, params, number_of_global_trials) + self.assertEqual(sol.number_of_local_trials, 70) + def test_XSquared_Solve(self): r = 3.5 problem = XSquared(1) From 519b4c55a031655d65bfabf92ab4178eb093b4ca Mon Sep 17 00:00:00 2001 From: Yanina Kolt <43132462+YaniKolt@users.noreply.github.com> Date: Thu, 14 Sep 2023 18:00:21 +0300 Subject: [PATCH 2/2] Problems with crit dis (#161) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Задачи с ограничениями и дискретными параметрами * Добавлены новые задачи с ограничениями и дискретными параметрами. Исправлены некоторые задачи по pep8 * Update problem.py * Update problem.py * removed comments * Update problem.py * Update problem.py --- examples/GKLS_example.py | 2 +- examples/GKLS_timeout_example.py | 2 +- problems/Floudas.py | 81 +++ problems/GKLS_function/gkls_function.py | 1 - problems/Pern.py | 80 +++ problems/Synthes.py | 95 ++++ problems/Yuan.py | 94 ++++ problems/ex1222.py | 81 +++ problems/gbd.py | 82 +++ problems/nvs21.py | 77 +++ problems/p1.py | 77 +++ problems/p2.py | 75 +++ problems/p7.py | 83 +++ problems/rastriginInt.py | 5 +- problems/rastrigin_int_hidden_constraint.py | 5 +- problems/romeijn2c.py | 4 +- problems/stronginc2.py | 3 +- problems/stronginc5.py | 2 +- test/problems/pointsForTest/Floudas_points.py | 112 +++++ test/problems/pointsForTest/Pern_points.py | 51 ++ test/problems/pointsForTest/Synthes_points.py | 316 ++++++++++++ test/problems/pointsForTest/Yuan_points.py | 223 ++++++++ test/problems/pointsForTest/ex1222_points.py | 130 +++++ test/problems/pointsForTest/g8c_points.py | 189 ++----- test/problems/pointsForTest/gbd_points.py | 74 +++ test/problems/pointsForTest/nvs21_points.py | 179 +++++++ test/problems/pointsForTest/p1_points.py | 37 ++ test/problems/pointsForTest/p2_points.py | 26 + test/problems/pointsForTest/p7_points.py | 100 ++++ .../pointsForTest/romeijn1c_points.py | 251 ++++----- .../pointsForTest/romeijn2c_points.py | 476 ++++-------------- .../pointsForTest/romeijn3c_points.py | 402 ++++----------- .../pointsForTest/romeijn5\321\201_points.py" | 243 +++------ test/problems/test_GKLS.py | 30 -- test/problems/test_all_problems.py | 192 +++++++ test/problems/test_g8c_problem.py | 30 -- test/problems/test_grishagin_problem.py | 27 - test/problems/test_rastriginInt_problem.py | 26 - test/problems/test_rastrigin_problem.py | 27 - test/problems/test_romeijn1c_problem.py | 37 -- test/problems/test_romeijn2c_problem.py | 34 -- test/problems/test_romeijn3c_problem.py | 34 -- .../test_romeijn5\321\201_problem.py" | 35 -- test/problems/test_shekel4_problem.py | 36 -- test/problems/test_stronginc2_problem.py | 31 -- test/problems/test_stronginc3_problem.py | 33 -- test/problems/test_stronginc5_problem.py | 35 -- 47 files changed, 2687 insertions(+), 1578 deletions(-) create mode 100644 problems/Floudas.py create mode 100644 problems/Pern.py create mode 100644 problems/Synthes.py create mode 100644 problems/Yuan.py create mode 100644 problems/ex1222.py create mode 100644 problems/gbd.py create mode 100644 problems/nvs21.py create mode 100644 problems/p1.py create mode 100644 problems/p2.py create mode 100644 problems/p7.py create mode 100644 test/problems/pointsForTest/Floudas_points.py create mode 100644 test/problems/pointsForTest/Pern_points.py create mode 100644 test/problems/pointsForTest/Synthes_points.py create mode 100644 test/problems/pointsForTest/Yuan_points.py create mode 100644 test/problems/pointsForTest/ex1222_points.py create mode 100644 test/problems/pointsForTest/gbd_points.py create mode 100644 test/problems/pointsForTest/nvs21_points.py create mode 100644 test/problems/pointsForTest/p1_points.py create mode 100644 test/problems/pointsForTest/p2_points.py create mode 100644 test/problems/pointsForTest/p7_points.py delete mode 100644 test/problems/test_GKLS.py create mode 100644 test/problems/test_all_problems.py delete mode 100644 test/problems/test_g8c_problem.py delete mode 100644 test/problems/test_grishagin_problem.py delete mode 100644 test/problems/test_rastriginInt_problem.py delete mode 100644 test/problems/test_rastrigin_problem.py delete mode 100644 test/problems/test_romeijn1c_problem.py delete mode 100644 test/problems/test_romeijn2c_problem.py delete mode 100644 test/problems/test_romeijn3c_problem.py delete mode 100644 "test/problems/test_romeijn5\321\201_problem.py" delete mode 100644 test/problems/test_shekel4_problem.py delete mode 100644 test/problems/test_stronginc2_problem.py delete mode 100644 test/problems/test_stronginc3_problem.py delete mode 100644 test/problems/test_stronginc5_problem.py diff --git a/examples/GKLS_example.py b/examples/GKLS_example.py index 55e9958..f762348 100644 --- a/examples/GKLS_example.py +++ b/examples/GKLS_example.py @@ -30,7 +30,7 @@ def SolveSingleGKLS(): solver.add_listener(spl) # Решение задачи - sol = solver.solve() + solver.solve() if __name__ == "__main__": diff --git a/examples/GKLS_timeout_example.py b/examples/GKLS_timeout_example.py index f746a2b..98a209c 100644 --- a/examples/GKLS_timeout_example.py +++ b/examples/GKLS_timeout_example.py @@ -24,7 +24,7 @@ def SolveSingleGKLS(): solver.add_listener(cfol) # Решение задачи - sol = solver.solve() + solver.solve() if __name__ == "__main__": diff --git a/problems/Floudas.py b/problems/Floudas.py new file mode 100644 index 0000000..b35b343 --- /dev/null +++ b/problems/Floudas.py @@ -0,0 +1,81 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class Floudas(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса Floudas problem. + """ + super(Floudas, self).__init__() + self.name = "Floudas" + self.dimension = 3 + self.number_of_float_variables = 2 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 3 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0.2 + self.lower_bound_of_float_variables[1] = -2.22554 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 1 + self.upper_bound_of_float_variables[1] = -1 + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv = [0.499609, -1.305787] + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 0.100001 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = point.discrete_variables + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(-0.7 * int(b[0]) + 5.0 * (x[0] - 0.5) * (x[0] - 0.5) + 0.8) + elif function_value.functionID == 0: # constraint 1 + result = np.double(-math.exp(x[0] - 0.2) - x[1]) + elif function_value.functionID == 1: # constraint 2 + result = np.double(x[1] + 1.1 * int(b[0]) - 1) + elif function_value.functionID == 2: # constraint 3 + result = np.double(x[0] - 1.2 * int(b[0]) - 0.2) + + function_value.value = result + return function_value diff --git a/problems/GKLS_function/gkls_function.py b/problems/GKLS_function/gkls_function.py index 8f3bc1b..280836d 100644 --- a/problems/GKLS_function/gkls_function.py +++ b/problems/GKLS_function/gkls_function.py @@ -1,5 +1,4 @@ import numpy as np -import math from problems.GKLS_function.gkls_random import GKLSRandomGenerator diff --git a/problems/Pern.py b/problems/Pern.py new file mode 100644 index 0000000..a84c1c6 --- /dev/null +++ b/problems/Pern.py @@ -0,0 +1,80 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class Pern(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса Pern problem. + """ + super(Pern, self).__init__() + self.name = "Pern" + self.dimension = 2 + self.number_of_float_variables = 1 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 3 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 1 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 10 + + self.discrete_variable_values = [[[str(i) for i in range(1, 7)]] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv[0] = 4 + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = -17 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables[0] + b = int(point.discrete_variables[0]) + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(3.0 * b - 5.0 * x) + elif function_value.functionID == 0: # constraint 1 + result = np.double(2.0 * b * b - 2.0 * math.sqrt(b) - 2.0 * math.sqrt(x) * b * b + + 11.0 * b + 8 * x - 39.0) + elif function_value.functionID == 1: # constraint 2 + result = np.double(-b + x - 3.0) + elif function_value.functionID == 2: # constraint 3 + result = np.double(2.0 * b + 3 * x - 24.0) + + function_value.value = result + return function_value diff --git a/problems/Synthes.py b/problems/Synthes.py new file mode 100644 index 0000000..5df3095 --- /dev/null +++ b/problems/Synthes.py @@ -0,0 +1,95 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class Synthes(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса Synthes problem. + """ + super(Synthes, self).__init__() + self.name = "Synthes" + self.dimension = 6 + self.number_of_float_variables = 3 + self.number_of_discrete_variables = 3 + self.number_of_objectives = 1 + self.number_of_constraints = 6 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables.fill(0) + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables.fill(3) + + self.discrete_variable_values = [[[str(i) for i in range(0, 6)]] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + # UNDEFINED + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = [int(x) for x in point.discrete_variables] + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(5.0 * b[0] + 6.0 * b[1] + 8.0 * b[2] + 10.0 * x[0] + - 7.0 * x[2] - 18.0 * math.log(x[1] + 1.0) + - 19.2 * math.log(x[0] - x[1] + 1.0) + 10.0) + elif function_value.functionID == 0: # constraint 1 + result = np.double(b[0] + b[1] - 1.1) + elif function_value.functionID == 1: # constraint 2 + if ((x[0] - x[1] + 1.0) != 0): + try: + result = np.double(-(math.log(x[1] + 1.0) + 1.2* + math.log(x[0] - x[1] + 1.0) - x[2]- 2 * b[2] + 2.0)) + except ValueError: + print("CalculateFuncs Error!!!") + result = np.NaN + pass # do nothing! + else: + result = 1 + elif function_value.functionID == 2: # constraint 3 + if ((x[0] - x[1] + 1.0) != 0): + try: + result = np.double(-(math.log(x[1] + 1.0) + 1.2* + math.log(x[0] - x[1] + 1.0) - x[2]- 2 * b[2] + 2.0)) + except ValueError: + print("CalculateFuncs Error!!!") + result = np.NaN + pass # do nothing! + + else: + result = 1 + elif function_value.functionID == 3: # constraint 4 + result = np.double(x[1] - x[0]) + elif function_value.functionID == 4: # constraint 5 + result = np.double(x[1] - 2.0 * b[0]) + elif function_value.functionID == 5: # constraint 6 + result = np.double(x[0] - x[1] - 2.0 * b[1]) + + function_value.value = result + return function_value diff --git a/problems/Yuan.py b/problems/Yuan.py new file mode 100644 index 0000000..0437198 --- /dev/null +++ b/problems/Yuan.py @@ -0,0 +1,94 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class Yuan(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса Yuan problem. + """ + super(Yuan, self).__init__() + self.name = "Yuan" + self.dimension = 7 + self.number_of_float_variables = 3 + self.number_of_discrete_variables = 4 + self.number_of_objectives = 1 + self.number_of_constraints = 9 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables.fill(0) + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables.fill(3) + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv = [0.2, 0.8, 1.908] + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv = ["1", "1", "0", "1"] + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 4.5796 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = [int(x) for x in point.discrete_variables] + + if function_value.type == FunctionType.OBJECTIV: + result = np.double((b[0] - 1.0) * (b[0] - 1.0) + (b[1] - 2.0) * (b[1] - 2.0) + + (b[2] - 1.0) * (b[2] - 1.0) - math.log(b[3] + 1.0) + + (x[0] - 1.0) * (x[0] - 1.0) + (x[1] - 2.0) * (x[1] - 2.0) + + (x[2] - 3.0) * (x[2] - 3.0)) + elif function_value.functionID == 0: # constraint 1 + result = np.double(b[0] + b[1] + b[2] + x[0] + x[1] + x[2] - 5.0) + elif function_value.functionID == 1: # constraint 2 + result = np.double(b[2] * b[2] + x[0] * x[0] + x[1] * x[1] + x[2] * x[2] - 5.5) + elif function_value.functionID == 2: # constraint 3 + result = np.double(b[0] + x[0] - 1.2) + elif function_value.functionID == 3: # constraint 4 + result = np.double(b[1] + x[1] - 1.8) + elif function_value.functionID == 4: # constraint 5 + result = np.double(b[2] + x[2] - 2.5) + elif function_value.functionID == 5: # constraint 6 + result = np.double(b[3] + x[0] - 1.2) + elif function_value.functionID == 6: # constraint 7 + result = np.double(b[1] * b[1] + x[1] * x[1] - 1.64) + elif function_value.functionID == 7: # constraint 8 + result = np.double(b[2] * b[2] + x[2] * x[2] - 4.25) + elif function_value.functionID == 8: # constraint 9 + result = np.double(b[1] * b[1] + x[2] * x[2] - 4.64) + + function_value.value = result + return function_value diff --git a/problems/ex1222.py b/problems/ex1222.py new file mode 100644 index 0000000..3993320 --- /dev/null +++ b/problems/ex1222.py @@ -0,0 +1,81 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class ex1222(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса Ex1222 problem. + """ + super(ex1222, self).__init__() + self.name = "ex1222" + self.dimension = 3 + self.number_of_float_variables = 2 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 3 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0.2 + self.lower_bound_of_float_variables[1] = -2.22554 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 1 + self.upper_bound_of_float_variables[1] = -1 + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv = [0.999609, -2.100473] + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = -3.634153 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = point.discrete_variables + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(- 5.0 * math.sqrt(x[0] - 0.5) + 0.7 * int(b[0]) - 0.8) + elif function_value.functionID == 0: # constraint 1 + result = np.double(-math.exp(x[0] - 0.2) - x[1]) + elif function_value.functionID == 1: # constraint 2 + result = np.double(x[1] + 1.1 * int(b[0]) + 1) + elif function_value.functionID == 2: # constraint 3 + result = np.double(x[0] - 1.2 * int(b[0])) + + function_value.value = result + return function_value diff --git a/problems/gbd.py b/problems/gbd.py new file mode 100644 index 0000000..9a9fc77 --- /dev/null +++ b/problems/gbd.py @@ -0,0 +1,82 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class gbd(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса gbd problem. + + """ + super(gbd, self).__init__() + self.name = "gbd" + self.dimension = 4 + self.number_of_float_variables = 1 + self.number_of_discrete_variables = 3 + self.number_of_objectives = 1 + self.number_of_constraints = 4 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0.2 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 1 + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv[0] = 0.666593 + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv.fill("1") + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = -7.082258 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = point.discrete_variables + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(-5.0 * math.sqrt(x[0]) - int(b[0]) - int(b[1]) - int(b[2])) + elif function_value.functionID == 0: # constraint 1 + result = np.double(3.0 * x[0] - int(b[0]) - int(b[1])) + elif function_value.functionID == 1: # constraint 2 + result = np.double(-x[0] + 0.1*int(b[1]) + 0.25*int(b[2])) + elif function_value.functionID == 2: # constraint 3 + result = np.double(-(int(b[0]) + int(b[1]) + int(b[2]) - 2.0)) + elif function_value.functionID == 3: # constraint 4 + result = np.double(-(int(b[0]) + int(b[1]) + 2.0*int(b[2]) - 2.0)) + + function_value.value = result + return function_value diff --git a/problems/nvs21.py b/problems/nvs21.py new file mode 100644 index 0000000..3305586 --- /dev/null +++ b/problems/nvs21.py @@ -0,0 +1,77 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class nvs21(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса nvs21 problem. + """ + super(nvs21, self).__init__() + self.name = "nvs21" + self.dimension = 3 + self.number_of_float_variables = 1 + self.number_of_discrete_variables = 2 + self.number_of_objectives = 1 + self.number_of_constraints = 2 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0.1 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 0.2 + + self.discrete_variable_values = [[str(i) for i in range(1, 201)] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv = [0.1] + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv.fill("1") + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 0.000636 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = point.discrete_variables + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(0.00201 * pow(int(b[0]), 4) * int(b[1]) * math.sqrt(x[0])) + elif function_value.functionID == 0: # constraint 1 + result = np.double(-(-math.sqrt(int(b[0])) * int(b[1]) + 675.0)) + elif function_value.functionID == 1: # constraint 2 + result = np.double(-(-0.1 * math.sqrt(int(b[0])) * math.sqrt(x[0]) + 0.419)) + + function_value.value = result + return function_value diff --git a/problems/p1.py b/problems/p1.py new file mode 100644 index 0000000..43640a5 --- /dev/null +++ b/problems/p1.py @@ -0,0 +1,77 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class p1(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса p1 problem. + """ + super(p1, self).__init__() + self.name = "p1" + self.dimension = 2 + self.number_of_float_variables = 1 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 2 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 1.6 + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv[0]= 0.5 + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 2 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables[0] + b = int(point.discrete_variables[0]) + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(2 * x + b) + elif function_value.functionID == 0: # constraint 1 + result = np.double(1.25 - x*x - b) + elif function_value.functionID == 1: # constraint 2 + result = np.double(x + b - 1.6) + + function_value.value = result + return function_value diff --git a/problems/p2.py b/problems/p2.py new file mode 100644 index 0000000..b1d991c --- /dev/null +++ b/problems/p2.py @@ -0,0 +1,75 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class p2(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса p2 problem. + """ + super(p2, self).__init__() + self.name = "p2" + self.dimension = 2 + self.number_of_float_variables = 1 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 1 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables[0] = 0.5 + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables[0] = 1.5 + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv[0]= 1.375 + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 2.124 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables[0] + b = int(point.discrete_variables[0]) + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(-b + 2 * x - math.log(x / 2.0)) + elif function_value.functionID == 0: # constraint 1 + result = np.double(-x - math.log(x / 2.0) + b) + + function_value.value = result + return function_value diff --git a/problems/p7.py b/problems/p7.py new file mode 100644 index 0000000..83f924a --- /dev/null +++ b/problems/p7.py @@ -0,0 +1,83 @@ +import numpy as np +from iOpt.trial import Point +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Trial +from iOpt.problem import Problem +import math + + +class p7(Problem): + """ + + """ + + def __init__(self): + """ + Конструктор класса p7 problem. + """ + super(p7, self).__init__() + self.name = "p7" + self.dimension = 3 + self.number_of_float_variables = 2 + self.number_of_discrete_variables = 1 + self.number_of_objectives = 1 + self.number_of_constraints = 4 + + self.float_variable_names = np.ndarray(shape=(self.number_of_float_variables,), dtype=object) + for i in range(self.number_of_float_variables): + self.float_variable_names[i] = str(i) + + self.discrete_variable_names = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + for i in range(self.number_of_discrete_variables): + self.discrete_variable_names[i] = str(i) + + self.lower_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.lower_bound_of_float_variables.fill(-0.01) + self.upper_bound_of_float_variables = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + self.upper_bound_of_float_variables.fill(4) + + self.discrete_variable_values = [["0", "1"] for i in range(self.number_of_discrete_variables)] + + self.known_optimum = np.ndarray(shape=(1,), dtype=Trial) + + pointfv = np.ndarray(shape=(self.number_of_float_variables,), dtype=np.double) + pointfv = [3.514237, 0] + + pointdv = np.ndarray(shape=(self.number_of_discrete_variables,), dtype=object) + pointdv[0] = "1" + + KOpoint = Point(pointfv, pointdv) + KOfunV = np.ndarray(shape=(1,), dtype=FunctionValue) + KOfunV[0] = FunctionValue() + KOfunV[0].value = 99.245209 + self.known_optimum[0] = Trial(KOpoint, KOfunV) + + + def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: + """ + Вычисление значения выбранной функции в заданной точке. + + :param point: координаты точки испытания, в которой будет вычислено значение функции + :param function_value: объект определяющий номер функции в задаче и хранящий значение функции + :return: Вычисленное значение функции в точке point + """ + result: np.double = 0 + x = point.float_variables + b = int(point.discrete_variables[0]) + + if function_value.type == FunctionType.OBJECTIV: + result = np.double(7.5 * b + 5.5 * (1 - b) + 7 * x[0] + 6 * x[1] + + 50 * (b / (2 * b - 1)) / (0.9 * (1 - math.exp(-0.5 * x[0]))) + + 50 * (1 - b / (2 * b - 1)) / (0.8 * (1 - math.exp(-0.4 * x[1])))) + elif function_value.functionID == 0: # constraint 1 + result = np.double(0.9 * (1 - math.exp(-0.5 * x[0])) - 2 * b) + elif function_value.functionID == 1: # constraint 2 + result = np.double(0.8 * (1 - math.exp(-0.4 * x[1])) - 2 * (1 - b)) + elif function_value.functionID == 2: # constraint 3 + result = np.double(x[0] - 10 * b - 0.01) + elif function_value.functionID == 3: # constraint 4 + result = np.double(x[1] - 10 * (1 - b)) + + function_value.value = result + return function_value diff --git a/problems/rastriginInt.py b/problems/rastriginInt.py index 9f8310b..6c4ea98 100644 --- a/problems/rastriginInt.py +++ b/problems/rastriginInt.py @@ -69,12 +69,13 @@ def __init__(self, dimension: int, number_of_discrete_variables: int): self.multKoef = 0 x = np.ndarray(shape=(self.dimension), dtype=np.double) - count =math.pow(2, self.dimension) + count = math.pow(2, self.dimension) for i in range(int(count)): for j in range(self.dimension): x[j] = self.A[j] if (((i >> j) & 1) == 0) else self.B[j] v = abs(self.MultFunc(x)) - if v > self.multKoef: self.multKoef = v + if v > self.multKoef: + self.multKoef = v self.multKoef += 4 self.optMultKoef = (self.MultFunc(self.optPoint)+self.multKoef) diff --git a/problems/rastrigin_int_hidden_constraint.py b/problems/rastrigin_int_hidden_constraint.py index a348585..2555c97 100644 --- a/problems/rastrigin_int_hidden_constraint.py +++ b/problems/rastrigin_int_hidden_constraint.py @@ -69,12 +69,13 @@ def __init__(self, dimension: int, number_of_discrete_variables: int): self.multKoef = 0 x = np.ndarray(shape=(self.dimension), dtype=np.double) - count =math.pow(2, self.dimension) + count = math.pow(2, self.dimension) for i in range(int(count)): for j in range(self.dimension): x[j] = self.A[j] if (((i >> j) & 1) == 0) else self.B[j] v = abs(self.mult_func(x)) - if v > self.multKoef: self.multKoef = v + if v > self.multKoef: + self.multKoef = v self.multKoef += 4 self.optMultKoef = (self.mult_func(self.optPoint) + self.multKoef) diff --git a/problems/romeijn2c.py b/problems/romeijn2c.py index 6eb0fd6..b9ce198 100644 --- a/problems/romeijn2c.py +++ b/problems/romeijn2c.py @@ -49,7 +49,7 @@ def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValu x = point.float_variables if function_value.type == FunctionType.OBJECTIV: - result = np.double(-(0.0204 + 0.0607 * pow(x[4], 2)) * x[0] * x[3] * (x[0] + x[1] + x[2]) - \ + result = np.double(-(0.0204 + 0.0607 * pow(x[4], 2)) * x[0] * x[3] * (x[0] + x[1] + x[2]) - (0.0187 + 0.0437 * pow(x[5], 2)) * x[1] * x[2] * (x[0] + 1.57 * x[1] + x[3])) elif function_value.functionID == 0: # constraint 1 for i in range(0, self.dimension): @@ -57,7 +57,7 @@ def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValu result = np.double(2070 * result - 1) elif function_value.functionID == 1: # constraint 2 - result = np.double(0.00062 * x[0] * x[3] * pow(x[4], 2) * (x[0] + x[1] + x[2]) + \ + result = np.double(0.00062 * x[0] * x[3] * pow(x[4], 2) * (x[0] + x[1] + x[2]) + 0.00058 * x[1] * x[2] * pow(x[5], 2) * (x[0] + 1.57 * x[1] + x[3]) - 1) function_value.value = result diff --git a/problems/stronginc2.py b/problems/stronginc2.py index 5785d2e..ccc0762 100644 --- a/problems/stronginc2.py +++ b/problems/stronginc2.py @@ -57,10 +57,9 @@ def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValu res = np.double(res + t1 * t2 * math.exp(2.0 - t1 - t2)) res = np.double(-res) elif function_value.functionID == 0: # constraint 1 - res = np.double(((x[0]- 2.2) * (x[0] - 2.2) + (x[1] - 1.2) * (x[1] - 1.2) - 1.25)) + res = np.double(((x[0] - 2.2) * (x[0] - 2.2) + (x[1] - 1.2) * (x[1] - 1.2) - 1.25)) elif function_value.functionID == 1: # constraint 2 res = np.double(1.21 - (x[0] - 2.2) * (x[0] - 2.2) - (x[1] - 1.2) * (x[1] - 1.2)) function_value.value = res return function_value - diff --git a/problems/stronginc5.py b/problems/stronginc5.py index f8f5a0b..727d4c7 100644 --- a/problems/stronginc5.py +++ b/problems/stronginc5.py @@ -35,7 +35,7 @@ def __init__(self): KOpoint = Point(pointfv, []) KOfunV = np.ndarray(shape=(1), dtype=FunctionValue) KOfunV[0] = FunctionValue() - KOfunV[0] = self.calculate(KOpoint, KOfunV[0]) # -43.298677; + KOfunV[0] = self.calculate(KOpoint, KOfunV[0]) # -43.298677; self.known_optimum[0] = Trial(KOpoint, KOfunV) def calculate(self, point: Point, function_value: FunctionValue) -> FunctionValue: diff --git a/test/problems/pointsForTest/Floudas_points.py b/test/problems/pointsForTest/Floudas_points.py new file mode 100644 index 0000000..ccf7e47 --- /dev/null +++ b/test/problems/pointsForTest/Floudas_points.py @@ -0,0 +1,112 @@ +import numpy as np + +test_points = np.array([[0.600390625, -1.612171592, 0, 0, 0.1197640363], + [0.600390625, -1.612171592, 1, 0, 0.1197640363], + [0.999609375, -1.613368408, 1, 0, -0.6113033381], + [0.999609375, -1.613368408, 1, 1, -1.513368408], + [0.999609375, -1.613368408, 1, 2, -0.400390625], + [0.999609375, -1.613368408, 1, 3, 1.348047638], + [0.200390625, -1.612171592, 0, 0, 0.6117808905], + [0.200390625, -1.612171592, 1, 0, 0.6117808905], + [0.999609375, -1.613368408, 0, 0, -0.6113033381], + [0.999609375, -1.613368408, 0, 1, -2.613368408], + [0.999609375, -1.613368408, 0, 2, 0.799609375], + [0.799609375, -1.919753408, 1, 0, 0.09834623397], + [0.800390625, -1.305786592, 1, 0, -0.5170441128], + [0.800390625, -1.305786592, 1, 1, -1.205786592], + [0.800390625, -1.305786592, 1, 2, -0.599609375], + [0.800390625, -1.305786592, 1, 3, 0.5511726379], + [0.600390625, -1.305786592, 1, 0, -0.1866209637], + [0.600390625, -1.305786592, 1, 1, -1.205786592], + [0.600390625, -1.305786592, 1, 2, -0.799609375], + [0.600390625, -1.305786592, 1, 3, 0.1503913879], + [0.800390625, -2.224941592, 1, 0, 0.4021108872], + [0.700390625, -1.458979092, 1, 0, -0.1903863365], + [0.700390625, -1.458979092, 1, 1, -1.358979092], + [0.700390625, -1.458979092, 1, 2, -0.699609375], + [0.700390625, -1.458979092, 1, 3, 0.3007820129], + [0.400390625, -1.918556592, 1, 0, 0.69667663], + [0.400390625, -1.918556592, 0, 0, 0.69667663], + [0.700390625, -1.612171592, 1, 0, -0.03719383645], + [0.700390625, -1.612171592, 1, 1, -1.512171592], + [0.700390625, -1.612171592, 1, 2, -0.699609375], + [0.700390625, -1.612171592, 1, 3, 0.3007820129], + [0.650390625, -1.535575342, 1, 0, -0.03334958531], + [0.650390625, -1.535575342, 1, 1, -1.435575342], + [0.650390625, -1.535575342, 1, 2, -0.749609375], + [0.650390625, -1.535575342, 1, 3, 0.2130867004], + [0.600390625, -1.535575342, 1, 0, 0.0431677863], + [0.677734375, -1.309377041, 1, 0, -0.3030400872], + [0.677734375, -1.309377041, 1, 1, -1.209377041], + [0.677734375, -1.309377041, 1, 2, -0.722265625], + [0.677734375, -1.309377041, 1, 3, 0.2579475403], + [0.655078125, -1.044880615, 1, 0, -0.5314159112], + [0.655078125, -1.044880615, 1, 1, -0.9448806152], + [0.655078125, -1.044880615, 1, 2, -0.744921875], + [0.655078125, -1.044880615, 1, 3, 0.2202461243], + [0.636328125, -1.158578174, 1, 0, -0.3884381524], + [0.636328125, -1.158578174, 1, 1, -1.058578174], + [0.636328125, -1.158578174, 1, 2, -0.763671875], + [0.636328125, -1.158578174, 1, 3, 0.1929267883], + [0.676953125, -1.261504385, 1, 0, -0.3496535345], + [0.676953125, -1.261504385, 1, 1, -1.161504385], + [0.676953125, -1.261504385, 1, 2, -0.723046875], + [0.676953125, -1.261504385, 1, 3, 0.2565620422], + [0.455859375, -1.026928369, 1, 0, -0.2646427188], + [0.455859375, -1.026928369, 1, 1, -0.9269283691], + [0.455859375, -1.026928369, 1, 2, -0.944140625], + [0.455859375, -1.026928369, 1, 3, 0.1097419739], + [0.225390625, -1.181317686, 1, 0, 0.1556019731], + [0.518359375, -1.345281533, 1, 0, -0.02958873325], + [0.518359375, -1.345281533, 1, 1, -1.245281533], + [0.518359375, -1.345281533, 1, 2, -0.881640625], + [0.518359375, -1.345281533, 1, 3, 0.1016853333], + [0.359765625, -1.196876299, 1, 0, 0.02364043722], + [0.408984375, -1.502064482, 1, 0, 0.2696387407], + [0.476171875, -1.262701201, 1, 0, -0.05537318742], + [0.476171875, -1.262701201, 1, 1, -1.162701201], + [0.476171875, -1.262701201, 1, 2, -0.923828125], + [0.476171875, -1.262701201, 1, 3, 0.1028388977], + [0.406640625, -1.397941455, 1, 0, 0.1684008289], + [0.362890625, -1.293818428, 1, 0, 0.1169104694], + [0.454296875, -1.340494268, 1, 0, 0.05093968361], + [0.560546875, -1.194482666, 1, 0, -0.2396308149], + [0.560546875, -1.194482666, 1, 1, -1.094482666], + [0.560546875, -1.194482666, 1, 2, -0.839453125], + [0.560546875, -1.194482666, 1, 3, 0.1183296204], + [0.404296875, -1.248339404, 1, 0, 0.02167713953], + [0.506640625, -1.323738838, 1, 0, -0.03511370479], + [0.506640625, -1.323738838, 1, 1, -1.223738838], + [0.506640625, -1.323738838, 1, 2, -0.893359375], + [0.506640625, -1.323738838, 1, 3, 0.1002204895], + [0.591796875, -1.304589775, 1, 0, -0.1750473542], + [0.591796875, -1.304589775, 1, 1, -1.204589775], + [0.591796875, -1.304589775, 1, 2, -0.808203125], + [0.591796875, -1.304589775, 1, 3, 0.1421333313], + [0.529296875, -1.035306084, 1, 0, -0.3546843638], + [0.529296875, -1.035306084, 1, 1, -0.935306084], + [0.529296875, -1.035306084, 1, 2, -0.870703125], + [0.529296875, -1.035306084, 1, 3, 0.1042915344], + [0.425390625, -1.303392959, 1, 0, 0.05058095867], + [0.419921875, -1.107115068, 0, 0, -0.1388643163], + [0.419921875, -1.107115068, 0, 1, -2.107115068], + [0.419921875, -1.107115068, 0, 2, 0.219921875], + [0.294921875, -1.192089033, 0, 0, 0.09251608557], + [0.525390625, -1.451798193, 0, 0, 0.0672268048], + [0.419140625, -1.15977499, 1, 0, -0.08523135316], + [0.419140625, -1.15977499, 1, 1, -1.05977499], + [0.419140625, -1.15977499, 1, 2, -0.980859375], + [0.419140625, -1.15977499, 1, 3, 0.1326911926], + [0.425390625, -1.490096318, 0, 0, 0.237284318], + [0.900390625, -2.071749092, 1, 0, 0.05720960852], + [0.999609375, -2.072945908, 1, 0, -0.1517258381], + [0.999609375, -2.072945908, 1, 1, -1.972945908], + [0.999609375, -2.072945908, 1, 2, -0.400390625], + [0.999609375, -2.072945908, 1, 3, 1.348047638], + [0.360546875, -1.140625928, 0, 0, -0.03352688253], + [0.360546875, -1.140625928, 0, 1, -2.140625928], + [0.360546875, -1.140625928, 0, 2, 0.160546875], + [0.487890625, -1.377595576, 1, 0, 0.04398414378], + [0.495703125, -1.122673682, 1, 0, -0.2213973949], + [0.495703125, -1.122673682, 1, 1, -1.022673682], + [0.495703125, -1.122673682, 1, 2, -0.904296875]]) diff --git a/test/problems/pointsForTest/Pern_points.py b/test/problems/pointsForTest/Pern_points.py new file mode 100644 index 0000000..9f6d9ae --- /dev/null +++ b/test/problems/pointsForTest/Pern_points.py @@ -0,0 +1,51 @@ +import numpy as np + +test_points = np.array([[5.5, 1, 0, 11.30958424], + [5.5, 2, 0, 13.40990984], + [5.5, 3, 0, 10.32215655], + [5.5, 4, 0, 1.953347843], + [5.5, 5, 0, -11.73252995], + [5.5, 5, 1, -2.5], + [5.5, 5, 2, 2.5], + [5.5, 6, 0, -30.75394684], + [5.5, 6, 1, -3.5], + [5.5, 6, 2, 4.5], + [7.75, 5, 0, -15.66624503], + [7.75, 5, 1, -0.25], + [7.75, 5, 2, 9.25], + [3.25, 5, 0, -2.610917842], + [3.25, 5, 1, -4.75], + [3.25, 5, 2, -4.25], + [3.25, 5, 3, -1.25], + [7.75, 6, 0, -44.33849655], + [7.75, 6, 1, -1.25], + [7.75, 6, 2, 11.25], + [3.25, 6, 0, -9.698825402], + [3.25, 6, 1, -5.75], + [3.25, 6, 2, -2.25], + [3.25, 6, 3, 1.75], + [4.375, 5, 0, -8.054639272], + [4.375, 5, 1, -3.625], + [4.375, 5, 2, -0.875], + [4.375, 5, 3, -6.875], + [2.125, 5, 0, 5.640965359], + [4.9375, 5, 0, -10.07456617], + [4.9375, 5, 1, -3.0625], + [4.9375, 5, 2, 0.8125], + [2.125, 6, 0, 6.143886407], + [4.375, 6, 0, -21.49778426], + [4.375, 6, 1, -4.625], + [4.375, 6, 2, 1.125], + [4.65625, 5, 0, -9.11386409], + [4.65625, 5, 1, -3.34375], + [4.65625, 5, 2, -0.03125], + [4.65625, 5, 3, -8.28125], + [4.796875, 5, 0, -9.60598263], + [4.796875, 5, 1, -3.203125], + [4.796875, 5, 2, 0.390625], + [4.7265625, 5, 0, -9.362930523], + [4.7265625, 5, 1, -3.2734375], + [4.7265625, 5, 2, 0.1796875], + [4.69140625, 5, 0, -9.239157525], + [4.69140625, 5, 1, -3.30859375], + [4.69140625, 5, 2, 0.07421875]]) diff --git a/test/problems/pointsForTest/Synthes_points.py b/test/problems/pointsForTest/Synthes_points.py new file mode 100644 index 0000000..c2333ce --- /dev/null +++ b/test/problems/pointsForTest/Synthes_points.py @@ -0,0 +1,316 @@ +import numpy as np + +test_points = np.array([[1.50146484375, 2.99853515625, 1.49853515625, 0, 0, 0, 0, -1.1000000000000001], + [1.50146484375, 2.99853515625, 1.49853515625, 1, 0, 0, 0, -0.10000000000000009], + [1.50146484375, 2.99853515625, 1.49853515625, 2, 0, 0, 0, 0.89999999999999991], + [1.50146484375, 2.99853515625, 1.49853515625, 3, 0, 0, 0, 1.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 4, 0, 0, 0, 2.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 5, 0, 0, 0, 3.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 0, 1, 0, 0, -0.10000000000000009], + [1.50146484375, 2.99853515625, 1.49853515625, 1, 1, 0, 0, 0.89999999999999991], + [1.50146484375, 2.99853515625, 1.49853515625, 2, 1, 0, 0, 1.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 3, 1, 0, 0, 2.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 4, 1, 0, 0, 3.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 5, 1, 0, 0, 4.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 0, 2, 0, 0, 0.89999999999999991], + [1.50146484375, 2.99853515625, 1.49853515625, 1, 2, 0, 0, 1.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 2, 2, 0, 0, 2.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 3, 2, 0, 0, 3.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 4, 2, 0, 0, 4.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 5, 2, 0, 0, 5.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 0, 3, 0, 0, 1.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 1, 3, 0, 0, 2.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 2, 3, 0, 0, 3.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 3, 3, 0, 0, 4.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 4, 3, 0, 0, 5.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 5, 3, 0, 0, 6.9000000000000004], + [1.50146484375, 2.99853515625, 1.49853515625, 0, 4, 0, 0, 2.8999999999999999], + [1.50146484375, 2.99853515625, 1.49853515625, 1, 4, 0, 0, 3.8999999999999999], + [1.50146484375, 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0, 1, 5, -0.1985351562], + [0.00146484375, 1.501464844, 1.501464844, 1, 0, 0, 1, 6, 0.614396677], + [2.998535156, 1.498535156, 1.501464844, 0, 1, 0, 1, 0, 1.998535156], + [2.998535156, 1.498535156, 1.501464844, 0, 0, 1, 0, 0, 1.998535156], + [2.998535156, 1.498535156, 1.501464844, 1, 0, 0, 0, 0, 1.998535156], + [2.998535156, 1.498535156, 1.501464844, 0, 1, 0, 0, 0, 1.998535156]]) diff --git a/test/problems/pointsForTest/ex1222_points.py b/test/problems/pointsForTest/ex1222_points.py new file mode 100644 index 0000000..4e0422e --- /dev/null +++ b/test/problems/pointsForTest/ex1222_points.py @@ -0,0 +1,130 @@ +import numpy as np + +test_points = np.array([[0.600390625, -1.612171592, 0, 0, 0.1197640363], + [0.600390625, -1.612171592, 1, 0, 0.1197640363], + [0.999609375, -1.613368408, 1, 0, -0.6113033381], + [0.999609375, -1.613368408, 1, 1, 0.4866315918], + [0.200390625, -1.612171592, 0, 0, 0.6117808905], + [0.200390625, -1.612171592, 1, 0, 0.6117808905], + [0.999609375, -1.613368408, 0, 0, -0.6113033381], + [0.999609375, -1.613368408, 0, 1, -0.6133684082], + [0.999609375, -1.613368408, 0, 2, 0.999609375], + [0.799609375, -1.919753408, 0, 0, 0.09834623397], + [0.800390625, -1.305786592, 0, 0, -0.5170441128], + [0.800390625, -1.305786592, 0, 1, -0.3057865918], + [0.800390625, -1.305786592, 0, 2, 0.800390625], + [0.600390625, -1.305786592, 0, 0, -0.1866209637], + [0.600390625, -1.305786592, 0, 1, -0.3057865918], + [0.600390625, -1.305786592, 0, 2, 0.600390625], + [0.800390625, -2.224941592, 0, 0, 0.4021108872], + [0.700390625, -1.458979092, 0, 0, -0.1903863365], + [0.700390625, -1.458979092, 0, 1, -0.4589790918], + [0.700390625, -1.458979092, 0, 2, 0.700390625], + [0.400390625, -1.918556592, 0, 0, 0.69667663], + [0.400390625, -1.918556592, 1, 0, 0.69667663], + [0.443359375, -1.220812627, 1, 0, -0.0547143073], + [0.443359375, -1.220812627, 1, 1, 0.879187373], + [0.443359375, -1.220812627, 0, 0, -0.0547143073], + [0.443359375, -1.220812627, 0, 1, -0.220812627], + [0.443359375, -1.220812627, 0, 2, 0.443359375], + [0.293359375, -1.230387158, 0, 0, 0.1325309517], + [0.550390625, -1.449404561, 0, 0, 0.02978258041], + [0.378515625, -1.032912451, 0, 0, -0.1625291107], + [0.378515625, -1.032912451, 0, 1, -0.03291245117], + [0.378515625, -1.032912451, 0, 2, 0.378515625], + [0.271484375, -1.067620127, 0, 0, -0.006481240783], + [0.271484375, -1.067620127, 0, 1, -0.06762012695], + [0.271484375, -1.067620127, 0, 2, 0.271484375], + [0.214453125, -1.164562256, 0, 0, 0.1500041794], + [0.204296875, -1.077194658, 0, 0, 0.0728885384], + [0.462109375, -1.505654932, 0, 0, 0.2059862457], + [0.799609375, -1.919753408, 1, 0, 0.09834623397], + [0.800390625, -2.224941592, 1, 0, 0.4021108872], + [0.800390625, -1.305786592, 1, 0, -0.5170441128], + [0.800390625, -1.305786592, 1, 1, 0.7942134082], + [0.900390625, -2.071749092, 1, 0, 0.05720960852], + [0.999609375, -2.072945908, 1, 0, -0.1517258381], + [0.999609375, -2.072945908, 1, 1, 0.0270540918], + [0.950390625, -1.995152842, 1, 0, -0.1226742895], + [0.950390625, -1.995152842, 1, 1, 0.1048471582], + [0.949609375, -2.149542158, 1, 0, 0.03336893323], + [0.900390625, -2.071749092, 0, 0, 0.05720960852], + [0.999609375, -2.072945908, 0, 0, -0.1517258381], + [0.999609375, -2.072945908, 0, 1, -1.072945908], + [0.999609375, -2.072945908, 0, 2, 0.999609375], + [0.237109375, -1.024534736, 0, 0, -0.01327178839], + [0.237109375, -1.024534736, 0, 1, -0.02453473633], + [0.237109375, -1.024534736, 0, 2, 0.237109375], + [0.950390625, -2.224941592, 1, 0, 0.1071144605], + [0.949609375, -2.072945908, 1, 0, -0.04322731677], + [0.949609375, -2.072945908, 1, 1, 0.0270540918], + [0.205859375, -1.032912451, 0, 0, 0.02703587646], + [0.400390625, -2.224941592, 0, 0, 1.00306163], + [0.400390625, -2.224941592, 1, 0, 1.00306163], + [0.216015625, -1.000598408, 0, 0, -0.01554615434], + [0.216015625, -1.000598408, 0, 1, -0.0005984082031], + [0.216015625, -1.000598408, 0, 2, 0.216015625], + [0.450390625, -1.332116553, 0, 0, 0.04758946564], + [0.516015625, -1.369217861, 0, 0, -0.002433826188], + [0.516015625, -1.369217861, 0, 1, -0.3692178613], + [0.516015625, -1.369217861, 0, 2, 0.516015625], + [0.924609375, -2.111244033, 1, 0, 0.04731931132], + [0.202734375, -1.005385674, 0, 0, 0.002647557015], + [0.578515625, -1.032912451, 0, 0, -0.4272031698], + [0.578515625, -1.032912451, 0, 1, -0.03291245117], + [0.578515625, -1.032912451, 0, 2, 0.578515625], + [0.621484375, -2.054993662, 0, 0, 0.5307712673], + [0.658984375, -2.027466885, 1, 0, 0.4450009082], + [0.544921875, -1.578660732, 0, 0, 0.1667811202], + [0.975390625, -2.186643467, 1, 0, 0.01520328644], + [0.999609375, -2.187840283, 1, 0, -0.03683146314], + [0.999609375, -2.187840283, 1, 1, -0.0878402832], + [0.999609375, -2.187840283, 1, 2, -0.200390625], + [0.999609375, -2.187840283, 1, 3, -3.634152568], + [0.987109375, -2.206989346, 1, 0, 0.009952915631], + [0.987890625, -2.167494404, 1, 0, -0.03125913114], + [0.987890625, -2.167494404, 1, 1, -0.0674944043], + [0.987890625, -2.167494404, 1, 2, -0.212109375], + [0.987890625, -2.167494404, 1, 3, -3.592458393], + [0.987109375, -2.187840283, 1, 0, -0.009196146869], + [0.987109375, -2.187840283, 1, 1, -0.0878402832], + [0.987109375, -2.187840283, 1, 2, -0.212890625], + [0.987109375, -2.187840283, 1, 3, -3.589661069], + [0.414453125, -1.430255498, 0, 0, 0.1910714652], + [0.803515625, -2.017892354, 0, 0, 0.1893563932], + [0.803515625, -2.017892354, 1, 0, 0.1893563932], + [0.390234375, -1.317754756, 0, 0, 0.1082217071], + [0.226171875, -1.40631917, 0, 0, 0.3798018039], + [0.987890625, -2.224941592, 1, 0, 0.02618805636], + [0.975390625, -2.167494404, 1, 0, -0.003945776061], + [0.975390625, -2.167494404, 1, 1, -0.0674944043], + [0.975390625, -2.167494404, 1, 2, -0.224609375], + [0.975390625, -2.167494404, 1, 3, -3.547428843], + [0.924609375, -2.072945908, 1, 0, 0.009021186317], + [0.884765625, -1.923343857, 1, 0, -0.05996308607], + [0.884765625, -1.923343857, 1, 1, 0.1766561426], + [0.884765625, -1.923343857, 0, 0, -0.05996308607], + [0.884765625, -1.923343857, 0, 1, -0.9233438574], + [0.884765625, -1.923343857, 0, 2, 0.884765625], + [0.555078125, -1.51283583, 0, 0, 0.08654375108], + [0.713671875, -1.997546475, 1, 0, 0.3261292985], + [0.994140625, -2.173478486, 1, 0, -0.03906029272], + [0.994140625, -2.173478486, 1, 1, -0.07347848633], + [0.994140625, -2.173478486, 1, 2, -0.205859375], + [0.994140625, -2.173478486, 1, 3, -3.614756837], + [0.989453125, -2.184249834, 1, 0, -0.01794193928], + [0.989453125, -2.184249834, 1, 1, -0.08424983398], + [0.989453125, -2.184249834, 1, 2, -0.210546875], + [0.989453125, -2.184249834, 1, 3, -3.59804633], + [0.980859375, -2.197414814, 1, 0, 0.01406704046], + [0.371484375, -1.478128154, 0, 0, 0.2910625596], + [0.588671875, -1.570283018, 0, 0, 0.09526253675], + [0.917578125, -2.175872119, 1, 0, 0.1264084687], + [0.995703125, -2.20220208, 1, 0, -0.01379649307], + [0.995703125, -2.20220208, 1, 1, -0.1022020801], + [0.995703125, -2.20220208, 1, 2, -0.204296875], + [0.995703125, -2.20220208, 1, 3, -3.620309379], + [0.995703125, -2.195021182, 1, 0, -0.02097739151], + [0.995703125, -2.195021182, 1, 1, -0.09502118164], + [0.995703125, -2.195021182, 1, 2, -0.204296875], + [0.995703125, -2.195021182, 1, 3, -3.620309379]]) diff --git a/test/problems/pointsForTest/g8c_points.py b/test/problems/pointsForTest/g8c_points.py index 63f8cc4..bc78504 100644 --- a/test/problems/pointsForTest/g8c_points.py +++ b/test/problems/pointsForTest/g8c_points.py @@ -1,178 +1,63 @@ import numpy as np -test_points = np.array([[5.004882813, 5.004882813, 0, 21.04396915], - [0.0048828125, 5.004882813, 0, -4.004858971], - [0.0048828125, 5.004882813, 1, 2.014791955], - [2.504882813, 2.504882813, 0, 4.769555092], - [2.504882813, 7.504882813, 0, -0.2304449081], - [2.504882813, 7.504882813, 1, 149.3967735], +test_points = np.array([[5.004882812, 5.004882812, 0, 21.04396915], + [0.0048828125, 5.004882812, 0, -4.004858971], + [0.0048828125, 5.004882812, 1, 2.014791955], + [2.504882812, 2.504882812, 0, 4.769555092], + [2.504882812, 7.504882812, 0, -0.2304449081], + [2.504882812, 7.504882812, 1, 149.3967735], [2.495117188, 4.995117188, 0, 2.230492592], [1.245117188, 3.745117188, 0, -1.194800377], [1.245117188, 3.745117188, 1, -0.240896704], - [1.245117188, 3.745117188, -1, 0.1036169237], - [2.504882813, 0.0048828125, 0, 7.269555092], + [1.245117188, 3.745117188, 2, 0.1036169237], + [2.504882812, 0.0048828125, 0, 7.269555092], [2.495117188, 3.745117188, 0, 3.480492592], [9.995117188, 4.995117188, 0, 95.9072504], - [1.254882813, 1.254882813, 0, 1.319848061], - [0.0048828125, 3.754882813, 0, -2.754858971], - [0.0048828125, 3.754882813, 1, 0.9987270866], - [0.0048828125, 1.254882813, 0, -0.2548589706], - [0.0048828125, 1.254882813, 1, 57.78141502], + [1.254882812, 1.254882812, 0, 1.319848061], + [0.0048828125, 3.754882812, 0, -2.754858971], + [0.0048828125, 3.754882812, 1, 0.9987270866], + [0.0048828125, 1.254882812, 0, -0.2548589706], + [0.0048828125, 1.254882812, 1, 57.78141502], [0.6201171875, 3.120117188, 0, -1.735571861], [0.6201171875, 3.120117188, 1, 0.9792587963], [1.870117188, 3.120117188, 0, 1.377221107], - [3.754882813, 3.842773438, 0, 11.2563715], + [3.754882812, 3.842773438, 0, 11.2563715], [1.245117188, 3.120117188, 0, -0.5698003769], [1.245117188, 3.120117188, 1, 0.3542587963], - [1.254882813, 3.129882813, 0, -0.5551519394], - [1.254882813, 3.129882813, 1, 0.3183235332], - [3.754882813, 1.323242188, 0, 13.77590275], - [1.567382813, 3.442382813, 0, 0.01430606842], + [1.254882812, 3.129882812, 0, -0.5551519394], + [1.254882812, 3.129882812, 1, 0.3183235332], + [3.754882812, 1.323242188, 0, 13.77590275], + [1.567382812, 3.442382812, 0, 0.01430606842], [0.9326171875, 3.432617188, 0, -1.562842369], [0.9326171875, 3.432617188, 1, 0.1710173952], - [2.446289063, 1.547851563, 0, 5.436478615], + [2.446289062, 1.547851562, 0, 5.436478615], [1.557617188, 2.807617188, 0, 0.6185541153], - [0.6298828125, 4.360351563, 0, -2.963599205], - [0.6298828125, 4.360351563, 1, 0.3869790537], + [0.6298828125, 4.360351562, 0, -2.963599205], + [0.6298828125, 4.360351562, 1, 0.3869790537], [1.557617188, 3.745117188, 0, -0.3189458847], [1.557617188, 3.745117188, 1, -0.553396704], - [1.557617188, 3.745117188, -1, -0.002215771701], - [1.977539063, 6.391601563, 0, -1.480940819], - [1.977539063, 6.391601563, 1, 31.7380929], + [1.557617188, 3.745117188, 2, -0.002215771701], + [1.977539062, 6.391601562, 0, -1.480940819], + [1.977539062, 6.391601562, 1, 31.7380929], [1.303710938, 5.249023438, 0, -2.549361229], [1.303710938, 5.249023438, 1, 2.130074854], - [0.7958984375, 5.708007813, 0, -4.07455349], - [0.7958984375, 5.708007813, 1, 8.714686518], - [3.569335938, 4.868164063, 0, 8.871994972], + [0.7958984375, 5.708007812, 0, -4.07455349], + [0.7958984375, 5.708007812, 1, 8.714686518], + [3.569335938, 4.868164062, 0, 8.871994972], [1.870117188, 4.409179688, 0, 0.08815860748], - [1.254882813, 2.817382813, 0, -0.2426519394], - [1.254882813, 2.817382813, 1, 1.701152748], - [1.567382813, 3.129882813, 0, 0.3268060684], + [1.254882812, 2.817382812, 0, -0.2426519394], + [1.254882812, 2.817382812, 1, 1.701152748], + [1.567382812, 3.129882812, 0, 0.3268060684], [3.647460938, 2.768554688, 0, 11.5354166], - [1.596679688, 1.918945313, 0, 1.630440712], - [0.6201171875, 3.754882813, 0, -2.370337486], - [0.6201171875, 3.754882813, 1, 0.3834927116], + [1.596679688, 1.918945312, 0, 1.630440712], + [0.6201171875, 3.754882812, 0, -2.370337486], + [0.6201171875, 3.754882812, 1, 0.3834927116], [0.0048828125, 3.120117188, 0, -2.120093346], [0.0048828125, 3.120117188, 1, 1.594493171], [4.995117188, 7.495117188, 0, 18.45607853], [0.6494140625, 4.995117188, 0, -3.573378563], [0.6494140625, 4.995117188, 1, 1.331197274], - [1.723632813, 3.598632813, 0, 0.3722772598], - [1.821289063, 4.926757813, 0, -0.6096639633], - [1.821289063, 4.926757813, 1, -0.08361413419], - [1.821289063, 4.926757813, -1, -0.007977492814], - [2.182617188, 4.633789063, 0, 1.130028725], - [1.528320313, 4.663085938, 0, -1.32732296], - [1.528320313, 4.663085938, 1, -0.3349992067], - [1.528320313, 4.663085938, -1, -0.0002144173608], - [1.928710938, 4.711914063, 0, 0.008011817932], - [1.547851563, 4.389648438, 0, -0.993803978], - [1.547851563, 4.389648438, 1, -0.5248004571], - [1.547851563, 4.389648438, -1, 0.0007539334198], - [2.084960938, 4.887695313, 0, 0.4593667984], - [1.694335938, 4.565429688, 0, -0.6946554184], - [1.694335938, 4.565429688, 1, -0.5921209857], - [1.694335938, 4.565429688, -1, -0.0108825067], - [2.397460938, 5.776367188, 0, 0.9714517593], - [2.309570313, 5.053710938, 0, 1.280404091], - [1.870117188, 5.209960938, 0, -0.7126226425], - [1.870117188, 5.209960938, 1, 1.273194829], - [1.987304688, 5.092773438, 0, -0.1433935165], - [1.987304688, 5.092773438, 1, 0.4386985764], - [3.579101563, 2.368164063, 0, 11.44180393], - [1.303710938, 5.786132813, 0, -3.086470604], - [1.303710938, 5.786132813, 1, 9.87411444], - [1.801757813, 6.166992188, 0, -1.920660973], - [1.801757813, 6.166992188, 1, 21.24929769], - [1.352539063, 1.723632813, 0, 1.105729103], - [0.1220703125, 5.717773438, 0, -4.702872276], - [0.1220703125, 5.717773438, 1, 9.584829181], - [0.9521484375, 5.541992188, 0, -3.63540554], - [0.9521484375, 5.541992188, 1, 5.701498625], - [1.791992188, 3.813476563, 0, 0.3977594376], - [2.182617188, 5.288085938, 0, 0.4757318497], - [1.840820313, 4.545898438, 0, -0.1572790146], - [1.840820313, 4.545898438, 1, -0.7520132705], - [1.840820313, 4.545898438, -1, -0.004254774966], - [1.411132813, 3.286132813, 0, -0.294836998], - [1.411132813, 3.286132813, 1, -0.1514341689], - [1.411132813, 3.286132813, -1, -0.01097757067], - [1.557617188, 3.276367188, 0, 0.1498041153], - [1.254882813, 3.286132813, 0, -0.7114019394], - [1.254882813, 3.286132813, 1, 0.004815831068], - [0.9423828125, 4.057617188, 0, -2.169531822], - [0.9423828125, 4.057617188, 1, 0.05762820818], - [2.446289063, 3.051757813, 0, 3.932572365], - [1.967773438, 4.956054688, 0, -0.08392238617], - [1.967773438, 4.956054688, 1, -0.1323032821], - [1.967773438, 4.956054688, -1, -4.202953182e-05], - [3.041992188, 4.184570313, 0, 6.069146156], - [0.9423828125, 2.807617188, 0, -0.9195318222], - [0.9423828125, 2.807617188, 1, 2.079066376], - [0.3173828125, 4.067382813, 0, -2.966650963], - [0.3173828125, 4.067382813, 1, 0.6826378031], - [0.9423828125, 4.672851563, 0, -2.784766197], - [0.9423828125, 4.672851563, 1, 0.2625809388], - [1.538085938, 4.155273438, 0, -0.7895650864], - [1.538085938, 4.155273438, 1, -0.5375046531], - [1.538085938, 4.155273438, -1, 0.0005322533008], - [1.508789063, 3.881835938, 0, -0.6053915024], - [1.508789063, 3.881835938, 1, -0.5085941042], - [1.508789063, 3.881835938, -1, -6.140256698e-06], - [1.635742188, 4.311523438, 0, -0.6358709335], - [1.635742188, 4.311523438, 1, -0.626324096], - [1.635742188, 4.311523438, -1, 0.01520392707], - [1.645507813, 4.028320313, 0, -0.3206243515], - [1.645507813, 4.028320313, 1, -0.6455071692], - [1.645507813, 4.028320313, -1, 0.003479833451], - [1.772460938, 4.194335938, 0, -0.05271816254], - [1.772460938, 4.194335938, 1, -0.7710346323], - [1.772460938, 4.194335938, -1, 0.02744029978], - [1.499023438, 4.985351563, 0, -1.738280296], - [1.499023438, 4.985351563, 1, 0.443657746], - [1.674804688, 4.809570313, 0, -1.004599571], - [1.674804688, 4.809570313, 1, -0.2452501652], - [1.674804688, 4.809570313, -1, -0.02157282794], - [1.391601563, 4.799804688, 0, -1.863249779], - [1.391601563, 4.799804688, 1, 0.01759858396], - [1.596679688, 4.907226563, 0, -1.357840538], - [1.596679688, 4.907226563, 1, 0.08074813488], - [0.3173828125, 2.807617188, 0, -1.706885338], - [0.3173828125, 2.807617188, 1, 2.704066376], - [0.3173828125, 3.442382813, 0, -2.341650963], - [0.3173828125, 3.442382813, 1, 0.7792989606], - [3.666992188, 0.2587890625, 0, 14.18804264], - [0.3271484375, 4.672851563, 0, -3.565825462], - [0.3271484375, 4.672851563, 1, 0.8778153138], - [1.401367188, 2.651367188, 0, 0.3124628067], - [1.811523438, 0.7080078125, 0, 3.573609352], - [1.713867188, 3.745117188, 0, 0.1922235489], - [2.163085938, 5.366210938, 0, 0.3127298355], - [1.430664063, 4.692382813, 0, -1.645583153], - [1.430664063, 4.692382813, 1, -0.2008454945], - [1.430664063, 4.692382813, -1, 0.003919714549], - [2.319335938, 2.006835938, 0, 4.372483253], - [1.616210938, 4.711914063, 0, -1.099776268], - [1.616210938, 4.711914063, 1, -0.3593427704], - [1.616210938, 4.711914063, -1, -0.01079077708], - [1.831054688, 4.008789063, 0, 0.3439722061], - [0.8935546875, 5.083007813, 0, -3.284567833], - [0.8935546875, 5.083007813, 1, 1.482153614], - [1.586914063, 1.420898438, 0, 2.097397804], - [1.528320313, 2.368164063, 0, 0.9675989151], - [1.987304688, 5.288085938, 0, -0.3387060165], - [1.987304688, 5.288085938, 1, 1.765525079], - [0.9326171875, 3.754882813, 0, -1.885107994], - [0.9326171875, 3.754882813, 1, 0.07099271157], - [0.9521484375, 4.370117188, 0, -2.46353054], - [0.9521484375, 4.370117188, 1, 0.06661692738], - [1.489257813, 3.364257813, 0, -0.1463689804], - [1.489257813, 3.364257813, 1, -0.325905936], - [1.489257813, 3.364257813, -1, -1.441335262e-05], - [1.333007813, 3.364257813, 0, -0.5873479843], - [1.333007813, 3.364257813, 1, -0.169655936], - [1.333007813, 3.364257813, -1, -0.04412515883], - [0.9326171875, 3.129882813, 0, -1.260107994], - [0.9326171875, 3.129882813, 1, 0.6405891582], - [0.9228515625, 4.389648438, 0, -2.537993431], - [0.9228515625, 4.389648438, 1, 0.1001995429]], dtype=np.double) + [1.723632812, 3.598632812, 0, 0.3722772598], + [1.821289062, 4.926757812, 0, -0.6096639633], + [1.821289062, 4.926757812, 1, -0.08361413419], + [1.821289062, 4.926757812, 2, -0.007977492814]], dtype=np.double) diff --git a/test/problems/pointsForTest/gbd_points.py b/test/problems/pointsForTest/gbd_points.py new file mode 100644 index 0000000..991830a --- /dev/null +++ b/test/problems/pointsForTest/gbd_points.py @@ -0,0 +1,74 @@ +import numpy as np + +test_points = np.array([[0.6, 0, 0, 0, 0, 1.8], + [0.6, 1, 0, 0, 0, 0.8], + [0.6, 0, 1, 0, 0, 0.8], + [0.6, 1, 1, 0, 0, -0.2], + [0.6, 1, 1, 0, 1, -0.5], + [0.6, 1, 1, 0, 2, -0], + [0.6, 1, 1, 0, 3, -0], + [0.6, 1, 1, 0, 4, -5.872983346], + [0.6, 0, 0, 1, 0, 1.8], + [0.6, 1, 0, 1, 0, 0.8], + [0.6, 0, 1, 1, 0, 0.8], + [0.6, 1, 1, 1, 0, -0.2], + [0.6, 1, 1, 1, 1, -0.25], + [0.6, 1, 1, 1, 2, -1], + [0.6, 1, 1, 1, 3, -2], + [0.6, 1, 1, 1, 4, -6.872983346], + [0.8, 1, 1, 1, 0, 0.4], + [0.4, 1, 1, 1, 0, -0.8], + [0.4, 1, 1, 1, 1, -0.05], + [0.4, 1, 1, 1, 2, -1], + [0.4, 1, 1, 1, 3, -2], + [0.4, 1, 1, 1, 4, -6.16227766], + [0.7, 1, 1, 1, 0, 0.1], + [0.8, 0, 1, 1, 0, 1.4], + [0.8, 0, 1, 0, 0, 1.4], + [0.4, 0, 1, 0, 0, 0.2], + [0.4, 0, 1, 1, 0, 0.2], + [0.8, 1, 0, 1, 0, 1.4], + [0.4, 1, 0, 1, 0, 0.2], + [0.8, 1, 0, 0, 0, 1.4], + [0.4, 1, 0, 0, 0, 0.2], + [0.4, 1, 1, 0, 0, -0.8], + [0.4, 1, 1, 0, 1, -0.3], + [0.4, 1, 1, 0, 2, -0], + [0.4, 1, 1, 0, 3, -0], + [0.4, 1, 1, 0, 4, -5.16227766], + [0.8, 1, 1, 0, 0, 0.4], + [0.3, 1, 0, 0, 0, -0.1], + [0.3, 1, 0, 0, 1, -0.3], + [0.3, 1, 0, 0, 2, 1], + [0.3, 0, 1, 0, 0, -0.1], + [0.3, 0, 1, 0, 1, -0.2], + [0.3, 0, 1, 0, 2, 1], + [0.3, 0, 1, 1, 0, -0.1], + [0.3, 0, 1, 1, 1, 0.05], + [0.3, 1, 0, 1, 0, -0.1], + [0.3, 1, 0, 1, 1, -0.05], + [0.3, 1, 0, 1, 2, -0], + [0.3, 1, 0, 1, 3, -1], + [0.3, 1, 0, 1, 4, -4.738612788], + [0.65, 1, 1, 1, 0, -0.05], + [0.65, 1, 1, 1, 1, -0.3], + [0.65, 1, 1, 1, 2, -1], + [0.65, 1, 1, 1, 3, -2], + [0.65, 1, 1, 1, 4, -7.031128874], + [0.9, 1, 1, 1, 0, 0.7], + [0.9, 1, 1, 0, 0, 0.7], + [0.35, 0, 1, 1, 0, 0.05], + [0.25, 0, 1, 1, 0, -0.25], + [0.25, 0, 1, 1, 1, 0.1], + [0.675, 1, 1, 1, 0, 0.025], + [0.6625, 1, 1, 1, 0, -0.0125], + [0.6625, 1, 1, 1, 1, -0.3125], + [0.6625, 1, 1, 1, 2, -1], + [0.6625, 1, 1, 1, 3, -2], + [0.6625, 1, 1, 1, 4, -7.069705149], + [0.66875, 1, 1, 1, 0, 0.00625], + [0.665625, 1, 1, 1, 0, -0.003125], + [0.665625, 1, 1, 1, 1, -0.315625], + [0.665625, 1, 1, 1, 2, -1], + [0.665625, 1, 1, 1, 3, -2], + [0.665625, 1, 1, 1, 4, -7.079292218]]) diff --git a/test/problems/pointsForTest/nvs21_points.py b/test/problems/pointsForTest/nvs21_points.py new file mode 100644 index 0000000..fdc6c19 --- /dev/null +++ b/test/problems/pointsForTest/nvs21_points.py @@ -0,0 +1,179 @@ +import numpy as np + +test_points = np.array([[0.15, 47, 1, 0, -668.1443454], + [0.15, 3, 2, 2, 0.1261120837], + [0.15, 194, 3, 1, 0.1204441584], + [0.15, 20, 4, 2, 498.2205777], + [0.15, 69, 4, 0, -641.7735045], + [0.15, 9, 6, 2, 30.64523634], + [0.15, 55, 6, 2, 42740.9031882614], + [0.15, 56, 6, 0, -630.1001114], + [0.15, 85, 6, 2, 243819.614451662], + [0.15, 87, 6, 1, -0.05775216264], + [0.15, 72, 8, 2, 167363.850752093], + [0.15, 39, 13, 2, 23412.2669501776], + [0.15, 76, 13, 0, -561.6686275], + [0.15, 186, 13, 1, 0.1092045058], + [0.15, 196, 15, 1, 0.1232176685], + [0.15, 182, 16, 1, 0.1034940191], + [0.15, 96, 17, 2, 1124023.88653258], + [0.15, 186, 19, 0, -415.8745478], + [0.15, 192, 20, 0, -397.8718708], + [0.15, 7, 21, 2, 39.25121835], + [0.15, 18, 23, 2, 1879.57449575105], + [0.15, 70, 23, 2, 429894.296248501], + [0.15, 134, 23, 1, 0.02933023543], + [0.15, 109, 25, 0, -413.9923373], + [0.15, 47, 28, 1, -0.1534816391], + [0.15, 10, 29, 1, -0.2965255129], + [0.15, 26, 29, 0, -527.1284341], + [0.15, 140, 30, 0, -320.035213], + [0.15, 118, 31, 0, -338.2538048], + [0.15, 121, 31, 1, 0.007028168083], + [0.15, 27, 34, 0, -498.3308176], + [0.15, 95, 35, 1, -0.04150827824], + [0.15, 124, 36, 0, -274.1209659], + [0.15, 92, 37, 2, 2063453.66114363], + [0.15, 115, 37, 2, 5037728.66490144], + [0.15, 158, 37, 0, -209.9172117], + [0.15, 140, 38, 0, -225.3779365], + [0.15, 28, 41, 2, 19618.1327540185], + [0.15, 141, 41, 0, -188.1519744], + [0.15, 39, 42, 0, -412.7100841], + [0.15, 74, 45, 2, 1050463.77304565], + [0.15, 50, 46, 1, -0.1451387212], + [0.15, 25, 47, 0, -440], + [0.15, 149, 47, 1, 0.05375786614], + [0.15, 65, 48, 1, -0.1067501001], + [0.15, 43, 49, 2, 130410.208510086], + [0.15, 54, 49, 2, 324349.18146243], + [0.15, 68, 52, 1, -0.09962561155], + [0.15, 76, 52, 1, -0.08136113968], + [0.15, 35, 54, 1, -0.1898712153], + [0.15, 195, 54, 0, 79.06896236], + [0.15, 41, 55, 1, -0.1710080646], + [0.15, 1, 56, 1, -0.3802701665], + [0.15, 190, 61, 0, 165.8269739], + [0.15, 109, 62, 1, -0.01464866762], + [0.15, 9, 63, 1, -0.3028104996], + [0.15, 32, 63, 2, 51425.9294492028], + [0.15, 98, 63, 0, -51.33181899], + [0.15, 109, 63, 1, -0.01464866762], + [0.15, 58, 64, 1, -0.1240423759], + [0.15, 19, 66, 2, 6695.76227726211], + [0.15, 78, 66, 1, -0.07694737247], + [0.15, 127, 69, 0, 102.5905092], + [0.15, 36, 70, 1, -0.1866209992], + [0.15, 4, 73, 0, -529], + [0.15, 50, 73, 2, 355176.778993134], + [0.15, 34, 74, 2, 76981.9796028714], + [0.15, 52, 74, 0, -141.3784112], + [0.15, 193, 75, 0, 366.9332992], + [0.15, 16, 78, 0, -363], + [0.15, 8, 82, 0, -443.0689758], + [0.15, 73, 83, 0, 34.15231086], + [0.15, 18, 84, 0, -318.6181823], + [0.15, 45, 86, 1, -0.1591923789], + [0.15, 56, 86, 2, 658403.674866573], + [0.15, 193, 86, 0, 519.7501831], + [0.15, 22, 89, 0, -257.5529974], + [0.15, 113, 89, 0, 271.0829773], + [0.15, 4, 90, 0, -495], + [0.15, 190, 90, 0, 565.5643877], + [0.15, 38, 94, 1, -0.1802532723], + [0.15, 168, 94, 0, 543.3792513], + [0.15, 28, 97, 0, -161.7242457], + [0.15, 42, 97, 1, -0.168001992], + [0.15, 37, 99, 2, 144438.768793777], + [0.15, 45, 100, 1, -0.1591923789], + [0.15, 18, 105, 0, -229.5227279], + [0.15, 113, 110, 0, 494.3160394], + [0.15, 17, 116, 2, 7542.15340703808], + [0.15, 116, 119, 0, 606.6692241], + [0.15, 102, 124, 0, 577.3386124], + [0.15, 47, 137, 0, 264.2246803], + [0.15, 1, 139, 0, -536], + [0.15, 10, 140, 0, -232.2811276], + [0.15, 88, 140, 0, 638.3164128], + [0.15, 13, 143, 1, -0.2793575996], + [0.15, 197, 143, 0, 1332.1006452094], + [0.15, 165, 144, 0, 1174.71349132778], + [0.15, 16, 145, 0, -95], + [0.15, 18, 148, 1, -0.2546832327], + [0.15, 167, 148, 0, 1237.58150153137], + [0.15, 138, 151, 0, 1098.84835879508], + [0.15, 123, 153, 0, 1021.85208548064], + [0.15, 16, 158, 2, 8060.81037001393], + [0.15, 13, 162, 1, -0.2793575996], + [0.15, 134, 163, 0, 1211.86141515481], + [0.15, 171, 173, 0, 1587.26855169761], + [0.15, 195, 174, 0, 1754.7777676158], + [0.15, 166, 175, 0, 1579.7172771769], + [0.15, 40, 178, 0, 450.770847], + [0.15, 80, 180, 0, 934.9689438], + [0.15, 120, 180, 0, 1296.8012070186], + [0.15, 94, 181, 0, 1079.86010838471], + [0.15, 34, 182, 0, 386.2332449], + [0.15, 38, 183, 0, 453.0877625], + [0.15, 12, 184, 2, 2970.19179575474], + [0.15, 62, 188, 0, 805.3134803], + [0.15, 49, 190, 0, 655], + [0.15, 65, 193, 0, 881.0157454], + [0.15, 73, 197, 0, 1008.16873782755], + [0.15, 163, 199, 0, 1865.66192162594], + [0.125, 118, 61, 0, -12.37039004], + [0.125, 119, 30, 2, 4275236.69622038], + [0.125, 121, 4, 0, -631], + [0.175, 122, 29, 1, 0.04306060209], + [0.175, 124, 35, 1, 0.04683258795], + [0.125, 125, 16, 2, 2775946.54333], + [0.125, 127, 24, 0, -404.5337359], + [0.125, 128, 14, 1, -0.019], + [0.125, 129, 45, 2, 8855690.27651637], + [0.125, 130, 54, 1, -0.01588711259], + [0.125, 130, 41, 0, -207.5280757], + [0.125, 131, 53, 0, -68.38727346], + [0.175, 139, 56, 0, -14.76973714], + [0.175, 139, 52, 1, 0.07420381183], + [0.175, 139, 10, 0, -557.1017388], + [0.125, 142, 15, 0, -496.2543707], + [0.125, 143, 13, 0, -519.5426103], + [0.1125, 143, 12, 2, 3382966.63527561], + [0.1125, 144, 56, 2, 16233430.799768], + [0.125, 150, 48, 0, -87.12246173], + [0.125, 150, 42, 0, -160.607154], + [0.1125, 148, 2, 0, -650.6689499], + [0.1125, 148, 27, 0, -346.5308234], + [0.1125, 150, 36, 1, -0.008208081871], + [0.1125, 151, 32, 0, -281.7774167], + [0.1125, 151, 49, 2, 17174187.0185926], + [0.125, 160, 39, 0, -181.684685], + [0.175, 162, 48, 0, -64.05974105], + [0.125, 163, 21, 0, -406.889948], + [0.175, 164, 40, 1, 0.1167238094], + [0.10625, 159, 13, 0, -511.0762372], + [0.175, 169, 34, 0, -233], + [0.1125, 163, 25, 1, 0.009223072709], + [0.175, 171, 46, 0, -73.47194579], + [0.1875, 119, 57, 1, 0.05336109069], + [0.125, 174, 20, 0, -411.1818808], + [0.10625, 165, 28, 1, -0.0002966443889], + [0.1875, 120, 3, 1, 0.05534164903], + [0.1125, 168, 21, 1, 0.01574130239], + [0.125, 178, 12, 0, -514.9000312], + [0.125, 178, 19, 0, -421.5083828], + [0.1125, 170, 38, 1, 0.01832139211], + [0.10625, 167, 28, 0, -313.1602565], + [0.103125, 166, 1, 0, -662.1159013], + [0.1587608017, 118, 33, 1, 0.01382530654], + [0.158756117, 119, 2, 1, 0.01564902998], + [0.125, 184, 43, 1, 0.06058315233], + [0.125, 185, 43, 0, -90.13676812], + [0.1588279602, 121, 37, 0, -268], + [0.103125, 171, 2, 1, 0.0009330303751], + [0.10625, 173, 39, 0, -162.0350889], + [0.1125, 177, 23, 1, 0.02723424342], + [0.175, 187, 12, 1, 0.1530576894], + [0.1125, 178, 40, 0, -141.3334374], + [0.1015625, 172, 27, 0, -320.8983197], + [0.1331391658, 146, 15, 0, -493.7543104]]) diff --git a/test/problems/pointsForTest/p1_points.py b/test/problems/pointsForTest/p1_points.py new file mode 100644 index 0000000..9b79ff4 --- /dev/null +++ b/test/problems/pointsForTest/p1_points.py @@ -0,0 +1,37 @@ +import numpy as np + +test_points = np.array([[0.8, 0, 0, 0.61], + [0.8, 1, 0, -0.39], + [0.8, 1, 1, 0.2], + [1.2, 1, 0, -1.19], + [1.2, 1, 1, 0.6], + [0.4, 1, 0, 0.09], + [0.6, 1, 0, -0.11], + [0.6, 1, 1, 0], + [0.6, 1, 2, 2.2], + [0.2, 1, 0, 0.21], + [0.7, 1, 0, -0.24], + [0.7, 1, 1, 0.1], + [0.5, 1, 0, 0], + [0.5, 1, 1, -0.1], + [0.5, 1, 2, 2], + [0.45, 1, 0, 0.0475], + [0.4, 0, 0, 1.09], + [1.2, 0, 0, -0.19], + [1.2, 0, 1, -0.4], + [1.2, 0, 2, 2.4], + [1.4, 0, 0, -0.71], + [1.4, 0, 1, -0.2], + [1.4, 0, 2, 2.8], + [1, 0, 0, 0.25], + [0.1, 1, 0, 0.24], + [0.475, 1, 0, 0.024375], + [0.3118577075, 1, 0, 0.1527447703], + [1.1, 0, 0, 0.04], + [0.4875, 1, 0, 0.01234375], + [0.5282608696, 1, 0, -0.02905954631], + [0.5282608696, 1, 1, -0.07173913043], + [0.5282608696, 1, 2, 2.056521739], + [0.65, 1, 0, -0.1725], + [0.65, 1, 1, 0.05], + [0.49375, 1, 0, 0.0062109375]]) diff --git a/test/problems/pointsForTest/p2_points.py b/test/problems/pointsForTest/p2_points.py new file mode 100644 index 0000000..bd00a5f --- /dev/null +++ b/test/problems/pointsForTest/p2_points.py @@ -0,0 +1,26 @@ +import numpy as np + +test_points = np.array([[1, 0, 0, -0.3068528194], + [1, 0, 1, 2.693147181], + [1, 1, 0, 0.6931471806], + [0.75, 0, 0, 0.230829253], + [1.25, 0, 0, -0.7799963708], + [1.25, 0, 1, 2.970003629], + [0.875, 0, 0, -0.04832142682], + [0.875, 0, 1, 2.576678573], + [1.25, 1, 0, 0.2200036292], + [0.75, 1, 0, 1.230829253], + [1.375, 1, 0, -0.0003065505586], + [1.375, 1, 1, 2.124693449], + [0.625, 0, 0, 0.5381508098], + [1.4375, 1, 0, -0.1072583131], + [1.4375, 1, 1, 2.205241687], + [1.3125, 1, 0, 0.1087134651], + [1.34375, 1, 0, 0.05393296767], + [1.359375, 1, 0, 0.02674714527], + [1.3671875, 1, 0, 0.01320397056], + [1.392663043, 1, 0, -0.03073363576], + [1.392663043, 1, 1, 2.147255495], + [1.46875, 1, 0, -0.1600145184], + [1.46875, 1, 1, 2.246235482], + [1.37109375, 1, 0, 0.006444651574]]) diff --git a/test/problems/pointsForTest/p7_points.py b/test/problems/pointsForTest/p7_points.py new file mode 100644 index 0000000..56349fa --- /dev/null +++ b/test/problems/pointsForTest/p7_points.py @@ -0,0 +1,100 @@ +import numpy as np + +test_points = np.array([[1.996958008, 1.996958008, 0, 0, 0.5684045309], + [1.996958008, 1.996958008, 1, 0, -1.431595469], + [1.996958008, 1.996958008, 1, 1, 0.4400991688], + [3.998041992, 1.993041992, 1, 0, -1.221921058], + [3.998041992, 1.993041992, 1, 1, 0.4395349762], + [2.995541992, 0.9905419922, 1, 0, -1.301265266], + [2.995541992, 0.9905419922, 1, 1, 0.2617113552], + [-0.008041992187, 1.996958008, 1, 0, -2.003626182], + [-0.008041992187, 1.996958008, 1, 1, 0.4400991688], + [2.999458008, -0.008041992187, 1, 0, -1.300871572], + [2.999458008, -0.008041992187, 1, 1, -0.002577581055], + [2.999458008, -0.008041992187, 1, 2, -7.010541992], + [2.999458008, -0.008041992187, 1, 3, -0.008041992187], + [2.999458008, -0.008041992187, 1, 4, 99.96557234], + [3.500708008, 0.4932080078, 1, 0, -1.256341194], + [3.500708008, 0.4932080078, 1, 1, 0.143233518], + [2.494291992, 0.4892919922, 1, 0, -1.358591286], + [2.494291992, 0.4892919922, 1, 1, 0.1422039487], + [-0.008041992187, 1.996958008, 0, 0, -0.00362618203], + [-0.008041992187, 1.996958008, 0, 1, -1.559900831], + [-0.008041992187, 1.996958008, 0, 2, -0.01804199219], + [-0.008041992187, 1.996958008, 0, 3, -8.003041992], + [-0.008041992187, 1.996958008, 0, 4, 131.0362117], + [3.998041992, 1.993041992, 0, 0, 0.7780789423], + [2.999458008, 0.4932080078, 1, 0, -1.300871572], + [2.999458008, 0.4932080078, 1, 1, 0.143233518], + [2.498208008, -0.008041992187, 1, 0, -1.358085457], + [2.498208008, -0.008041992187, 1, 1, -0.002577581055], + [2.498208008, -0.008041992187, 1, 2, -7.511791992], + [2.498208008, -0.008041992187, 1, 3, -0.008041992187], + [2.498208008, -0.008041992187, 1, 4, 102.8311923], + [3.250083008, 0.2425830078, 1, 0, -1.277213152], + [3.250083008, 0.2425830078, 1, 1, 0.07397930165], + [3.250083008, -0.008041992187, 1, 0, -1.277213152], + [3.250083008, -0.008041992187, 1, 1, -0.002577581055], + [3.250083008, -0.008041992187, 1, 2, -6.759916992], + [3.250083008, -0.008041992187, 1, 3, -0.008041992187], + [3.250083008, -0.008041992187, 1, 4, 99.37901677], + [3.375395508, 0.1172705078, 1, 0, -1.26645034], + [3.375395508, 0.1172705078, 1, 1, 0.03666001292], + [3.375395508, -0.008041992187, 1, 0, -1.26645034], + [3.375395508, -0.008041992187, 1, 1, -0.002577581055], + [3.375395508, -0.008041992187, 1, 2, -6.634604492], + [3.375395508, -0.008041992187, 1, 3, -0.008041992187], + [3.375395508, -0.008041992187, 1, 4, 99.24122774], + [0.9944580078, 0.9944580078, 1, 0, -1.647392316], + [0.9944580078, 0.9944580078, 1, 1, 0.2625538739], + [0.9944580078, -0.008041992187, 1, 0, -1.647392316], + [0.9944580078, -0.008041992187, 1, 1, -0.002577581055], + [0.9944580078, -0.008041992187, 1, 2, -9.015541992], + [0.9944580078, -0.008041992187, 1, 3, -0.008041992187], + [0.9944580078, -0.008041992187, 1, 4, 156.2136076], + [3.438051758, 0.05461425781, 1, 0, -1.261316599], + [3.438051758, 0.05461425781, 1, 1, 0.01728705111], + [3.998041992, 0.4892919922, 1, 0, -1.221921058], + [3.998041992, 0.4892919922, 1, 1, 0.1422039487], + [3.438051758, -0.008041992187, 1, 0, -1.261316599], + [3.438051758, -0.008041992187, 1, 1, -0.002577581055], + [3.438051758, -0.008041992187, 1, 2, -6.571948242], + [3.438051758, -0.008041992187, 1, 3, -0.008041992187], + [3.438051758, -0.008041992187, 1, 4, 99.20610754], + [3.469379883, 0.02328613281, 1, 0, -1.258809413], + [3.469379883, 0.02328613281, 1, 1, 0.007416966383], + [3.183510742, 0.1485986328, 1, 0, -1.283211165], + [3.183510742, 0.1485986328, 1, 1, 0.04616593221], + [3.234418945, 0.07027832031, 1, 0, -1.278606541], + [3.234418945, 0.07027832031, 1, 1, 0.02217590508], + [3.16784668, 0.02328613281, 1, 0, -1.284651714], + [3.16784668, 0.02328613281, 1, 1, 0.007416966383], + [3.04253418, 0.1290185547, 1, 0, -1.296591441], + [3.04253418, 0.1290185547, 1, 1, 0.0402386994], + [3.207006836, -0.004125976562, 1, 0, -1.281071385], + [3.207006836, -0.004125976562, 1, 1, -0.001321402615], + [3.207006836, -0.004125976562, 1, 2, -6.802993164], + [3.207006836, -0.004125976562, 1, 3, -0.004125976562], + [3.207006836, -0.004125976562, 1, 4, 99.47222617], + [3.320571289, 0.06244628906, 1, 0, -1.271076208], + [3.320571289, 0.06244628906, 1, 1, 0.01973530706], + [3.363647461, 0.05069824219, 1, 0, -1.267430951], + [3.363647461, 0.05069824219, 1, 1, 0.01606004391], + [3.250083008, 0.06244628906, 1, 0, -1.277213152], + [3.250083008, 0.06244628906, 1, 1, 0.01973530706], + [3.336235352, 0.01545410156, 1, 0, -1.269741567], + [3.336235352, 0.01545410156, 1, 1, 0.004930058875], + [3.469379883, -0.008041992187, 1, 0, -1.258809413], + [3.469379883, -0.008041992187, 1, 1, -0.002577581055], + [3.469379883, -0.008041992187, 1, 2, -6.540620117], + [3.469379883, -0.008041992187, 1, 3, -0.008041992187], + [3.469379883, -0.008041992187, 1, 4, 99.19643985], + [3.344067383, -0.004125976562, 1, 0, -1.269078156], + [3.344067383, -0.004125976562, 1, 1, -0.001321402615], + [3.344067383, -0.004125976562, 1, 2, -6.665932617], + [3.344067383, -0.004125976562, 1, 3, -0.004125976562], + [3.344067383, -0.004125976562, 1, 4, 99.29048248], + [3.285327148, 0.02720214844, 1, 0, -1.274117645], + [3.285327148, 0.02720214844, 1, 1, 0.008657501556], + [3.485043945, 0.007622070313, 1, 0, -1.257570471], + [3.485043945, 0.007622070313, 1, 1, 0.002435348135]]) diff --git a/test/problems/pointsForTest/romeijn1c_points.py b/test/problems/pointsForTest/romeijn1c_points.py index ebb4d78..c826a76 100644 --- a/test/problems/pointsForTest/romeijn1c_points.py +++ b/test/problems/pointsForTest/romeijn1c_points.py @@ -1,126 +1,133 @@ import numpy as np test_points = np.array( - [[0.0938165283203, 0.162220751953, 0.214020791016, 2, 10.161222328], - [9.15283203125e-05, 0.0812292480469, 0.214439208984, 2, -0.410672157258], - [9.15283203125e-05, 7.9248046875e-05, 0.214439208984, 2, -0.748585155246], - [0.0467709716797, 0.0810707519531, 0.107324208984, 2, 0.712090798772], - [0.0469540283203, 0.0404957519531, 0.214020791016, 2, 0.0711054129161], - [0.0467709716797, 7.9248046875e-05, 0.214020791016, 2, -0.665173740745], - [9.15283203125e-05, 0.162220751953, 0.214020791016, 2, 0.423950967866], - [0.0469540283203, 0.0406542480469, 0.000209208984375, 2, -0.201779486554], - [0.18735847168, 0.0810707519531, 0.214439208984, 2, 18.8478633916], - [0.0936334716797, 0.121804248047, 0.321135791016, 2, 7.65213256324], - [0.0469540283203, 0.0812292480469, 0.321554208984, 2, 1.27786079925], - [0.0725819580078, 0.0303520019531, 0.224481240234, 2, 0.605415300569], - [0.0335908935547, 0.00404165039062, 0.365906513672, 2, -0.181333196478], - [0.0601341064453, 0.0771083496094, 0.365906513672, 2, 2.11939104851], - [0.0507982177734, 0.0798027832031, 0.209836611328, 2, 1.10516766047], - [0.00997658691406, 0.0674400878906, 0.334525166016, 2, -0.0429365255276], - [9.15283203125e-05, 0.0812292480469, 0.321554208984, 2, -0.0721175579343], - [0.0469540283203, 7.9248046875e-05, 0.000209208984375, 2, -0.915276430734], - [0.0467709716797, 0.0810707519531, 0.000209208984375, 2, 0.623430251603], - [0.0894231689453, 0.0628437011719, 0.216949716797, 2, 3.07840805855], - [0.0868603759766, 0.0587228027344, 0.164229052734, 2, 2.53350760437], - [0.0819178466797, 0.00816254882813, 0.405656220703, 2, 0.50793029164], - [0.0601341064453, 0.0197327636719, 0.260465185547, 2, 0.0293931045706], - [0.0237058349609, 0.0409712402344, 0.0525114550781, 2, -0.686530334692], - [0.0244380615234, 0.0428731933594, 0.162973798828, 2, -0.514848523188], - [0.0892401123047, 0.0130759277344, 0.273017724609, 2, 0.38793368579], - [0.0647105224609, 0.0217932128906, 0.301051728516, 2, 0.31256495072], - [0.0240719482422, 0.0282915527344, 0.281804501953, 2, -0.342556628771], - [0.0643444091797, 0.00134721679687, 0.291009697266, 2, -0.350909495072], - [0.0782567138672, 0.0127589355469, 0.257954677734, 2, 0.118386655714], - [0.0410962158203, 0.0568208496094, 0.329504150391, 2, 0.553041912079], - [0.0268177978516, 0.105637646484, 0.0663192480469, 2, 0.137242612945], - [0.0147360595703, 0.152552490234, 0.0211301074219, 2, 0.276724268256], - [0.0108918701172, 0.132264990234, 0.0223853613281, 2, -0.0986740469059], - [0.0167496826172, 0.126717626953, 0.128245107422, 2, 0.129159175884], - [0.0183971923828, 0.145103173828, 0.150839677734, 2, 0.487357698721], - [0.0352384033203, 0.133849951172, 0.189334130859, 2, 1.2868769509], - [0.0244380615234, 0.142567236328, 0.134102958984, 2, 0.6912775354], - [0.00997658691406, 0.150967529297, 0.0592061425781, 2, 0.142524885169], - [0.0253533447266, 0.137019873047, 0.350843466797, 2, 1.30732582137], - [0.0290144775391, 0.150650537109, 0.293520205078, 2, 1.5339676636], - [0.0132716064453, 0.129412060547, 0.227828583984, 2, 0.288329622918], - [0.0368859130859, 0.148273095703, 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0.1721789941, 0, 1.54738281], + [0.03249255371, 0.0774253418, 0.4249034473, 0, 0.9994183988], + [0.09290124512, 0.007687060547, 0.2520968262, 0, 0.08501425367], + [0.04127927246, 0.1349594238, 0.1269898535, 0, 1.612148037], + [0.007596850586, 0.1240231934, 0.254188916, 0, 0.1739000136], + [0.02919753418, 0.05159047852, 0.4035641309, 0, 0.4465379209], + [0.04933376465, 0.05222446289, 0.1884972949, 0, 0.3344406578], + [0.02608557129, 0.04160522461, 0.3567013184, 0, 0.07412749901], + [0.02077692871, 0.1348009277, 0.2374521973, 0, 0.6516704688] ], dtype=np.double) diff --git a/test/problems/pointsForTest/romeijn2c_points.py b/test/problems/pointsForTest/romeijn2c_points.py index 477806e..cc477e2 100644 --- a/test/problems/pointsForTest/romeijn2c_points.py +++ b/test/problems/pointsForTest/romeijn2c_points.py @@ -1,436 +1,152 @@ import numpy as np test_points = np.array( - [[9.9951171875, 0.0048828125, 14.9926757813, 14.9926757813, 0.99951171875, 0.50048828125, 2, 376.200539414], - [9.9951171875, 4.9951171875, 14.9926757813, 11.2573242188, 0.99951171875, 0.25048828125, 2, -0.0188234798584], - [9.9951171875, 4.9951171875, 14.9926757813, 11.2573242188, 0.99951171875, 0.25048828125, 2, -0.0188234798584], - [9.9951171875, 4.9951171875, 14.9926757813, 11.2573242188, 0.99951171875, 0.25048828125, 2, -0.0188234798584], - [9.9951171875, 2.4951171875, 7.50732421875, 14.9926757813, 0.99951171875, 0.25048828125, 2, 1.94545154431], - [9.9951171875, 2.5048828125, 7.50732421875, 7.50732421875, 0.99951171875, 0.25048828125, 2, 4.85934938054], - [5.0048828125, 4.9951171875, 11.2573242188, 7.50732421875, 0.99951171875, 0.25048828125, 2, 2.91322754102], - [5.0048828125, 4.9951171875, 11.2426757813, 14.9926757813, 0.99951171875, 0.25048828125, 2, 0.96203437423], - [7.4951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.50048828125, 0.25048828125, 2, 0.96203437423], - [7.5048828125, 4.9951171875, 14.9926757813, 7.50732421875, 0.50048828125, 0.25048828125, 2, 2.91322754102], - [9.9951171875, 4.9951171875, 14.9926757813, 7.50732421875, 0.75048828125, 0.24951171875, 2, 0.967150506883], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.24951171875, 2, -0.0136998492095], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.24951171875, 2, -0.0136998492095], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.24951171875, 2, -0.0136998492095], - [9.9951171875, 4.9951171875, 14.9926757813, 7.50732421875, 0.99951171875, 0.25048828125, 2, 0.47128615752], - [9.9951171875, 2.5048828125, 14.9926757813, 9.38232421875, 0.99951171875, 0.37451171875, 2, 0.570189809157], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.74951171875, 2, -0.671661643613], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.74951171875, 2, -0.671661643613], - [9.9951171875, 4.9951171875, 14.9926757813, 14.9926757813, 0.74951171875, 0.74951171875, 2, 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0.00732421875, 0.2504882813, 0.00048828125, 1, -0.9999982036], - [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.2504882813, 0.00048828125, 3, + [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.2504882813, 0.00048828125, 1, -0.9999982036], - [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 1, -0.9999999995], - [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 1, -0.9999999995], - [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 0.00732421875, 0.9995117188, 0.4995117188, 1, -0.9999999995], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 1, -0.9999991471], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 1, -0.9999991471], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 3, + [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.9995117188, 0.5004882813, 1, -0.9999991471], - [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 3, -1], - [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 3, -1], - [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 3, -1], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.00048828125, 0.4995117188, 3, - -0.9999999223], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.00048828125, 0.4995117188, 3, + [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 1, -1], + [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 1, -1], + [2.504882813, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.00048828125, 1, -1], + [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.00048828125, 0.4995117188, 1, -0.9999999223], - [0.0048828125, 0.0048828125, 0.00732421875, 14.99267578, 0.00048828125, 0.4995117188, 3, - -0.9999999223], - [0.2099609375, 7.895507813, 4.812011719, 12.41455078, 0.2075195313, 0.03173828125, 3, - -0.9985456172], - [0.2099609375, 7.895507813, 4.812011719, 12.41455078, 0.2075195313, 0.03173828125, 3, - -0.9985456172], - [0.2099609375, 7.895507813, 4.812011719, 12.41455078, 0.2075195313, 0.03173828125, 3, - -0.9985456172], - [0.1611328125, 9.047851563, 3.083496094, 4.357910156, 0.8276367188, 0.3061523438, 3, - -0.967935716], - [0.1611328125, 9.047851563, 3.083496094, 4.357910156, 0.8276367188, 0.3061523438, 3, - -0.967935716], - [0.1611328125, 9.047851563, 3.083496094, 4.357910156, 0.8276367188, 0.3061523438, 3, - -0.967935716], - [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 3, + [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 1, -0.9838620511], - [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 3, + [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 1, -0.9838620511], - [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 3, + [2.397460938, 8.188476563, 0.6079101563, 2.116699219, 0.3051757813, 0.5063476563, 1, -0.9838620511], - [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 3, + [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 1, -0.7612414102], - [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 3, + [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 1, -0.7612414102], - [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 3, + [0.3271484375, 8.872070313, 1.970214844, 13.36669922, 0.5600585938, 0.9047851563, 1, -0.7612414102], - [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 3, + [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 1, -0.9998672736], - [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 3, + [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 1, -0.9998672736], - [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 3, + [9.995117188, 0.0048828125, 7.492675781, 14.99267578, 0.00048828125, 0.4995117188, 1, -0.9998672736], - [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 3, + [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 1, -0.5357944205], - [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 3, + [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 1, -0.5357944205], - [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 3, + [9.995117188, 0.0048828125, 0.00732421875, 7.492675781, 0.9995117188, 0.4995117188, 1, -0.5357944205], - [0.6103515625, 0.0341796875, 13.58642578, 8.635253906, 0.9643554688, 0.4926757813, 3, - -0.9561451154], - [0.6103515625, 0.0341796875, 13.58642578, 8.635253906, 0.9643554688, 0.4926757813, 3, - -0.9561451154], - [0.6103515625, 0.0341796875, 13.58642578, 8.635253906, 0.9643554688, 0.4926757813, 3, - -0.9561451154], - [1.215820313, 9.047851563, 12.28271484, 10.55419922, 0.8413085938, 0.2651367188, 3, - -0.7553408827], - [1.215820313, 9.047851563, 12.28271484, 10.55419922, 0.8413085938, 0.2651367188, 3, - -0.7553408827], - [1.215820313, 9.047851563, 12.28271484, 10.55419922, 0.8413085938, 0.2651367188, 3, - -0.7553408827], - [8.110351563, 8.520507813, 3.874511719, 14.69970703, 0.1928710938, 0.3940429688, 3, - -0.8360324241], - [8.110351563, 8.520507813, 3.874511719, 14.69970703, 0.1928710938, 0.3940429688, 3, - -0.8360324241], - [8.110351563, 8.520507813, 3.874511719, 14.69970703, 0.1928710938, 0.3940429688, 3, - -0.8360324241], - [0.4248046875, 0.4833984375, 14.69970703, 13.54248047, 0.4233398438, 0.5053710938, 3, - -0.9745221511], - [0.4248046875, 0.4833984375, 14.69970703, 13.54248047, 0.4233398438, 0.5053710938, 3, - -0.9745221511], - [0.4248046875, 0.4833984375, 14.69970703, 13.54248047, 0.4233398438, 0.5053710938, 3, - -0.9745221511], - [1.997070313, 9.165039063, 2.775878906, 0.5786132813, 0.2348632813, 0.3833007813, 3, - -0.962670955], - [1.997070313, 9.165039063, 2.775878906, 0.5786132813, 0.2348632813, 0.3833007813, 3, - -0.962670955], - [1.997070313, 9.165039063, 2.775878906, 0.5786132813, 0.2348632813, 0.3833007813, 3, - -0.962670955], - [0.6201171875, 0.6201171875, 14.23095703, 14.94873047, 0.07275390625, 0.3842773438, 3, - -0.9870260376], - [0.6201171875, 0.6201171875, 14.23095703, 14.94873047, 0.07275390625, 0.3842773438, 3, - -0.9870260376], - [0.6201171875, 0.6201171875, 14.23095703, 14.94873047, 0.07275390625, 0.3842773438, 3, - -0.9870260376], - [8.911132813, 8.745117188, 1.940917969, 5.749511719, 0.9526367188, 0.4428710938, 3, - -0.3802398165], - [8.911132813, 8.745117188, 1.940917969, 5.749511719, 0.9526367188, 0.4428710938, 3, - -0.3802398165], - [8.911132813, 8.745117188, 1.940917969, 5.749511719, 0.9526367188, 0.4428710938, 3, - -0.3802398165], - [9.018554688, 1.049804688, 13.96728516, 8.239746094, 0.8090820313, 0.4331054688, 3, - -0.2449301656], - [9.018554688, 1.049804688, 13.96728516, 8.239746094, 0.8090820313, 0.4331054688, 3, - -0.2449301656], - [9.018554688, 1.049804688, 13.96728516, 8.239746094, 0.8090820313, 0.4331054688, 3, - -0.2449301656], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.4995117188, 0.5004882813, 3, - -0.9998866166], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.4995117188, 0.5004882813, 3, - -0.9998866166], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.4995117188, 0.5004882813, 3, - -0.9998866166], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.4995117188, 3, - -0.9999999481], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.4995117188, 3, - -0.9999999481], - [9.995117188, 0.0048828125, 0.00732421875, 0.00732421875, 0.00048828125, 0.4995117188, 3, - -0.9999999481] + [1.997070313, 9.165039063, 2.775878906, 0.5786132813, 0.2348632813, 0.3833007813, 1, + -0.962670955] ], dtype=np.double) diff --git a/test/problems/pointsForTest/romeijn3c_points.py b/test/problems/pointsForTest/romeijn3c_points.py index d844dc9..df17676 100644 --- a/test/problems/pointsForTest/romeijn3c_points.py +++ b/test/problems/pointsForTest/romeijn3c_points.py @@ -1,319 +1,91 @@ import numpy as np test_points = np.array( - [[3.50634765625, 1.50537109375, 2, 0.01171875], - [-2.99365234375, 1.50537109375, 2, -6.48828125], - [-2.99365234375, 1.50537109375, 3, -5.25979447365], - [-2.99365234375, 1.50537109375, 4, -137.770705709], - [-2.99365234375, 1.50537109375, 1, 0.442135494892], - [9.99365234375, 1.49462890625, 2, 6.48828125], - [0.25634765625, -1.24462890625, 2, -5.98828125], - [0.25634765625, -1.24462890625, 3, -1.29275345802], - [0.25634765625, -1.24462890625, 4, -2.39433347851], - [0.25634765625, -1.24462890625, 1, 0.49024777988], - [0.25634765625, 4.25537109375, 2, -0.48828125], - [0.25634765625, 4.25537109375, 3, -17.8518354893], - [0.25634765625, 4.25537109375, 4, -28.8888647285], - [0.25634765625, 4.25537109375, 1, 3.99079562173], - [0.25634765625, -3.99462890625, 2, -8.73828125], - [0.25634765625, -3.99462890625, 3, -15.7007124424], - [0.25634765625, -3.99462890625, 4, -25.4470678535], - [0.25634765625, -3.99462890625, 1, 0.25458403192], - [-1.36865234375, -2.61962890625, 2, -8.98828125], - [-1.36865234375, -2.61962890625, 3, -8.23110795021], - [-1.36865234375, -2.61962890625, 4, -23.7987900403], - [-1.36865234375, -2.61962890625, 1, 0.283941976973], - [-2.99365234375, -2.61962890625, 2, -10.61328125], - [-2.99365234375, -2.61962890625, 3, -9.85610795021], - [-2.99365234375, -2.61962890625, 4, -145.124807271], - [-2.99365234375, -2.61962890625, 1, 0.227416890304], - [0.24365234375, 1.46240234375, 2, -3.2939453125], - [0.24365234375, 1.46240234375, 3, -1.89496827126], - [0.24365234375, 1.46240234375, 4, -3.34946909279], - [0.24365234375, 1.46240234375, 1, 1.0668839404], - [-2.18115234375, -3.30712890625, 2, -10.48828125], - [-2.18115234375, -3.30712890625, 3, -13.1182539463], - [-2.18115234375, -3.30712890625, 4, -69.3827119705], - [-2.18115234375, -3.30712890625, 1, 0.225670967726], - [1.95751953125, -2.72705078125, 2, -5.76953125], - [1.95751953125, -2.72705078125, 3, -5.47928643227], - [1.95751953125, -2.72705078125, 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[-2.993652344, 1.505371094, 0, -6.48828125], + [-2.993652344, 1.505371094, 1, -5.259794474], + [-2.993652344, 1.505371094, 2, -137.7707057], + [-2.993652344, 1.505371094, 3, 0.4421354949], + [9.993652344, 1.494628906, 0, 6.48828125], + [0.2563476562, -1.244628906, 0, -5.98828125], + [0.2563476562, -1.244628906, 1, -1.292753458], + [0.2563476562, -1.244628906, 2, -2.394333479], + [0.2563476562, -1.244628906, 3, 0.4902477799], + [0.2563476562, 4.255371094, 0, -0.48828125], + [0.2563476562, 4.255371094, 1, -17.85183549], + [0.2563476562, 4.255371094, 2, -28.88886473], + [0.2563476562, 4.255371094, 3, 3.990795622], + [0.2563476562, -3.994628906, 0, -8.73828125], + [0.2563476562, -3.994628906, 1, -15.70071244], + [0.2563476562, -3.994628906, 2, -25.44706785], + [0.2563476562, -3.994628906, 3, 0.2545840319], + [-1.368652344, -2.619628906, 0, -8.98828125], + [-1.368652344, -2.619628906, 1, -8.23110795], + [-1.368652344, -2.619628906, 2, -23.79879004], + [-1.368652344, -2.619628906, 3, 0.283941977], + [-2.993652344, -2.619628906, 0, -10.61328125], + [-2.993652344, -2.619628906, 1, -9.85610795], + [-2.993652344, -2.619628906, 2, -145.1248073], + [-2.993652344, -2.619628906, 3, 0.2274168903], + [0.2436523438, 1.462402344, 0, -3.293945312], + [0.2436523438, 1.462402344, 1, -1.894968271], + [0.2436523438, 1.462402344, 2, -3.349469093], + [0.2436523438, 1.462402344, 3, 1.06688394], + [-2.181152344, -3.307128906, 0, -10.48828125], + [-2.181152344, -3.307128906, 1, -13.11825395], + [-2.181152344, -3.307128906, 2, -69.38271197], + [-2.181152344, -3.307128906, 3, 0.2256709677], + [1.957519531, -2.727050781, 0, -5.76953125], + [1.957519531, -2.727050781, 1, -5.479286432], + [1.957519531, -2.727050781, 2, 25.60603674], + [1.779785156, -3.983886719, 0, -7.204101562], + [1.779785156, -3.983886719, 1, -14.09156823], + [1.779785156, -3.983886719, 2, 2.794385148], + [1.894042969, -1.330566406, 0, -4.436523438], + [1.894042969, -1.330566406, 1, 0.1236360073], + [1.005371094, -3.274902344, 0, -7.26953125], + [1.005371094, -3.274902344, 1, -9.719614267], + [1.005371094, -3.274902344, 2, -12.07897667], + [1.005371094, -3.274902344, 3, 0.318029036], + [1.119628906, -1.975097656, 0, -5.85546875], + [1.119628906, -1.975097656, 1, -2.781381845], + [1.119628906, -1.975097656, 2, 0.7760426105], + [-2.181152344, -3.994628906, 0, -11.17578125], + [-2.181152344, -3.994628906, 1, -18.13821244], + [-2.181152344, -3.994628906, 2, -77.41464556], + [-2.181152344, -3.994628906, 3, 0.2007715046], + [0.2309570312, -2.630371094, 0, -7.399414062], + [0.2309570312, -2.630371094, 1, -6.68789506], + [0.2309570312, -2.630371094, 2, -11.00856578], + [0.2309570312, -2.630371094, 3, 0.3445904384], + [-1.635253906, 0.00146484375, 0, -6.633789062], + [-1.635253906, 0.00146484375, 1, -1.635256052], + [-1.635253906, 0.00146484375, 2, -21.86380062], + [-1.635253906, 0.00146484375, 3, 0.4631976208], + [1.817871094, -3.231933594, 0, -6.4140625], + [1.817871094, -3.231933594, 1, -8.627523661], + [1.817871094, -3.231933594, 2, 13.32455524], + [1.779785156, -1.889160156, 0, -5.109375], + [1.779785156, -1.889160156, 1, -1.78914094], + [1.779785156, -1.889160156, 2, 22.47826881], + [2.097167969, -0.1596679688, 0, -3.0625], + [2.097167969, -0.1596679688, 1, 2.071674109], + [1.817871094, -0.9653320312, 0, -4.147460938], + [1.817871094, -0.9653320312, 1, 0.8860051632], + [2.224121094, 1.440917969, 0, -1.334960938], + [2.224121094, 1.440917969, 1, 0.1478765011], + [0.8911132812, -0.4711914062, 0, -4.580078125], + [0.8911132812, -0.4711914062, 1, 0.6690919399], + [4.369628906, 5.265136719, 0, 4.634765625], + [6.743652344, -1.255371094, 0, 0.48828125], + [6.756347656, -3.994628906, 0, -2.23828125], + [6.756347656, -3.994628906, 1, -9.200712442], + [6.756347656, -3.994628906, 2, 1516.545386], + [2.846191406, -1.964355469, 0, -4.118164062], + [2.846191406, -1.964355469, 1, -1.012501001], + [2.846191406, -1.964355469, 2, 109.1083074], + [-2.688964844, 0.2700195312, 0, -7.418945312], + [-2.688964844, 0.2700195312, 1, -2.761875391], + [-2.688964844, 0.2700195312, 2, -97.32988769], + [-2.688964844, 0.2700195312, 3, 0.3883026333] ], dtype=np.double) diff --git "a/test/problems/pointsForTest/romeijn5\321\201_points.py" "b/test/problems/pointsForTest/romeijn5\321\201_points.py" index 3a98ef6..42c0809 100644 --- "a/test/problems/pointsForTest/romeijn5\321\201_points.py" +++ "b/test/problems/pointsForTest/romeijn5\321\201_points.py" @@ -1,186 +1,65 @@ import numpy as np test_points = np.array( - [[1.00244140625, 7.50732421875, 2, -10.6565867763], - [1.00244140625, 7.50732421875, 3, 20.1114422187], - [-1.49755859375, 7.50732421875, 2, -2.8026051423], - [-1.49755859375, 7.50732421875, 3, 7.89491528673], - [-0.24755859375, 3.75732421875, 2, -2.97959595929], - [-0.24755859375, 3.75732421875, 3, 14.4244356294], - [3.49755859375, 7.49267578125, 2, -18.4805801649], - [3.49755859375, 7.49267578125, 3, -90.7633396187], - [3.49755859375, 7.49267578125, 1, -21.3744304354], - [2.24755859375, 3.74267578125, 2, -10.8035893479], - [2.24755859375, 3.74267578125, 3, -34.8857972705], - [2.24755859375, 3.74267578125, 1, -23.292083874], - [2.25244140625, 0.00732421875, 2, -7.08357759327], - [2.25244140625, 0.00732421875, 3, -50.0440649454], - [2.25244140625, 0.00732421875, 1, -18.1754553612], - [2.25244140625, 11.2573242188, 2, -18.3335775933], - [2.25244140625, 11.2573242188, 3, -5.04406494536], - [2.25244140625, 11.2573242188, 1, -117.756598457], - [1.00244140625, 11.2573242188, 2, -14.4065867763], - [1.00244140625, 11.2573242188, 3, 35.1114422187], - [-0.24755859375, 0.00732421875, 2, 0.770404040708], - [1.62744140625, 13.1323242188, 2, -18.2450821848], - [1.62744140625, 13.1323242188, 3, 26.3890028559], - [-0.87255859375, 1.88232421875, 2, 0.858899449202], - [-0.38427734375, 11.6967773438, 2, -10.4895344637], - [-0.38427734375, 11.6967773438, 3, 45.3296740035], - [0.37744140625, 1.88232421875, 2, -3.06809136779], - [0.37744140625, 1.88232421875, 3, 6.12325314327], - [2.24755859375, 13.1176757813, 2, -20.1785893479], - [2.24755859375, 13.1176757813, 3, 2.61420272947], - [0.37744140625, 0.00732421875, 2, -1.19309136779], - [0.37744140625, 0.00732421875, 3, -1.37674685673], - [0.37744140625, 0.00732421875, 1, -31.9857142472], - [-1.49755859375, 1.88232421875, 2, 2.8223948577], - [1.93505859375, 12.1801757813, 2, -18.2593416436], - [1.93505859375, 12.1801757813, 3, 11.7644455425], - [-0.32568359375, 7.43408203125, 2, -6.41091684573], - [-0.32568359375, 7.43408203125, 3, 28.6894611281], - [1.93994140625, 11.2573242188, 2, -17.351829889], - [1.93994140625, 11.2573242188, 3, 7.88629751005], - [-1.20458984375, 9.48486328125, 2, -5.70053267754], - [-1.20458984375, 9.48486328125, 3, 23.6182950068], - [2.09619140625, 11.7260742188, 2, -18.3114537411], - [2.09619140625, 11.7260742188, 3, 3.53707342105], - [2.94580078125, 14.2163085938, 2, -23.4708146871], - [2.94580078125, 14.2163085938, 3, -28.7806486562], - 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36.5028782318], - [-1.46826171875, 6.18896484375, 2, -1.57628461458], - [-1.46826171875, 6.18896484375, 3, 3.4790404784], - [0.48974609375, 3.74267578125, 2, -5.2812585115], - [0.48974609375, 3.74267578125, 3, 12.6034663072], - [-0.71630859375, 2.35107421875, 2, -0.100724402922], - [-0.71630859375, 2.35107421875, 3, 4.3402225814], - [2.79443359375, 14.7729492188, 2, -23.5519212678], - [2.79443359375, 14.7729492188, 3, -17.9785533633], - [2.79443359375, 14.7729492188, 1, -165.885572469], - [2.55517578125, 14.9340820313, 2, -22.9614034943], - [2.55517578125, 14.9340820313, 3, -4.70156174543], - [2.55517578125, 14.9340820313, 1, -187.517746731], - [-0.72607421875, 1.38427734375, 2, 0.896752087836], - [0.44580078125, 5.32470703125, 2, -6.72523149059], - [0.44580078125, 5.32470703125, 3, 19.3373593638], - [-1.12646484375, 6.93603515625, 2, -3.3971414786], - [-1.12646484375, 6.93603515625, 3, 15.2203721633], - [-1.31201171875, 3.91845703125, 2, 0.203349345799], - [-1.21923828125, 4.81201171875, 2, -0.9816616914], - [-1.21923828125, 4.81201171875, 3, 4.57646554298], - [-0.97998046875, 4.15283203125, 2, -1.07413258996], - [-0.97998046875, 4.15283203125, 3, 7.13293787522], - [-1.39013671875, 4.51904296875, 2, -0.15179966564], - [-1.39013671875, 4.51904296875, 3, -0.996642193563], - [-1.39013671875, 4.51904296875, 1, -125.464350753], - [-1.12158203125, 4.59228515625, 2, -1.06873128648], - [-1.12158203125, 4.59228515625, 3, 5.95370875181], - [-0.72607421875, 1.85302734375, 2, 0.428002087836], - [-0.71630859375, 1.88232421875, 2, 0.368025597078], - [0.71435546875, 2.38037109375, 2, -4.62458498643], - [0.71435546875, 2.38037109375, 3, 4.48498837892], - [0.62646484375, 2.08740234375, 2, -4.05549969461], - [0.62646484375, 2.08740234375, 3, 4.47620219255], - [2.25244140625, 14.7583007813, 2, -21.8345541558], - [2.25244140625, 14.7583007813, 3, 8.95984130464], - [1.74951171875, 9.26513671875, 2, -14.7613898817], - [1.74951171875, 9.26513671875, 3, 6.85174804328], - [1.66162109375, 7.71240234375, 2, -12.9325389649], - [1.66162109375, 7.71240234375, 3, 3.59978303127], - [0.24560546875, 8.59130859375, 2, -9.36290093006], - [0.24560546875, 8.59130859375, 3, 33.7698796416], - [-0.97998046875, 14.2016601563, 2, -11.122960715], - [-0.97998046875, 14.2016601563, 3, 47.3282503752], - [2.00830078125, 8.26904296875, 2, -14.5783059493], - [2.00830078125, 8.26904296875, 3, -6.73062748304], - [2.00830078125, 8.26904296875, 1, -70.9808644723], - [0.31396484375, 4.09423828125, 2, -5.08058792786], - [0.31396484375, 4.09423828125, 3, 15.4040674996], - [-0.48681640625, 5.23681640625, 2, -3.70743756073], - [-0.48681640625, 5.23681640625, 3, 18.6082659719], - [2.37939453125, 14.6411132813, 2, -22.1162016606], - [2.37939453125, 14.6411132813, 3, 2.68750684566], - [1.72021484375, 10.5249023438, 2, -15.9291166595], - [1.72021484375, 10.5249023438, 3, 12.8940770048], - [2.09619140625, 10.2905273438, 2, -16.8759068661], - [2.09619140625, 10.2905273438, 3, -2.20511407895], - [2.09619140625, 10.2905273438, 1, -103.239594856], - [1.40771484375, 8.67919921875, 2, -13.1016658302], - [1.40771484375, 8.67919921875, 3, 15.1585859454], - [-1.01416015625, 8.03466796875, 2, -4.84858987231], - [-1.01416015625, 8.03466796875, 3, 21.9875782384], - [2.42333984375, 14.9047851563, 2, -22.5179318065], - [2.42333984375, 14.9047851563, 3, 1.65913870638], - [0.47998046875, 7.36083984375, 2, -8.86874295824], - [0.47998046875, 7.36083984375, 3, 27.1695875723], - [1.93994140625, 14.4213867188, 2, -20.515892389], - [1.93994140625, 14.4213867188, 3, 20.5425475101], - [0.53369140625, 13.2348632813, 2, -14.9115042824], - [0.53369140625, 13.2348632813, 3, 50.1283280782], - [0.12353515625, 2.58544921875, 2, -2.97354635809], - [0.12353515625, 2.58544921875, 3, 10.1911774854], - [-0.73095703125, 4.13818359375, 2, -1.84181435429], - [-0.73095703125, 4.13818359375, 3, 11.279422691], - [-1.25830078125, 4.27001953125, 2, -0.316951040869], - [-1.25830078125, 4.27001953125, 3, 1.45332763535], - [1.97900390625, 12.9711914063, 2, -19.1884155396], - [1.97900390625, 12.9711914063, 3, 13.2308897013], - [2.48193359375, 14.7875976563, 2, -22.5848220011], - [2.48193359375, 14.7875976563, 3, -1.6463168585], - [2.48193359375, 14.7875976563, 1, -188.58762664], - [-1.18994140625, 4.03564453125, 2, -0.297333351173], - [-1.18994140625, 4.03564453125, 3, 2.16760764591], - [-0.26708984375, 2.79052734375, 2, -1.95143985278], - [-0.26708984375, 2.79052734375, 3, 10.4580415575], - [0.02099609375, 4.70947265625, 2, -4.77543383013], - [0.02099609375, 4.70947265625, 3, 18.8335397485], - [0.76318359375, 3.40576171875, 2, -5.80337369022], - [0.76318359375, 3.40576171875, 3, 7.87450370929], - [0.60693359375, 7.69775390625, 2, -9.60449202559], - [0.60693359375, 7.69775390625, 3, 27.1553653692], - [1.51513671875, 8.15185546875, 2, -12.9117978536], - [1.51513671875, 8.15185546875, 3, 9.9503703683], - [2.47216796875, 14.9487304688, 2, -22.7152751978], - [2.47216796875, 14.9487304688, 3, -0.524295153567], - [2.47216796875, 14.9487304688, 1, -193.554878053], - [-1.10205078125, 5.91064453125, 2, -2.44844989299], - [-1.10205078125, 5.91064453125, 3, 11.6557864118], - [-1.32666015625, 8.94287109375, 2, -4.77504529306], - [-1.32666015625, 8.94287109375, 3, 18.4007124701], - [-0.64794921875, 1.61865234375, 2, 0.416940161774], - [-0.63818359375, 2.11669921875, 2, -0.111786328983], - [-0.63818359375, 2.11669921875, 3, 4.44712117945], - [0.83642578125, 4.24072265625, 2, -6.8684317459], - [0.83642578125, 4.24072265625, 3, 10.0580355652], - [-1.37548828125, 5.48583984375, 2, -1.16461596428], - [-1.37548828125, 5.48583984375, 3, 3.27038355846], - [0.92919921875, 2.33642578125, 2, -5.2555912206], - [0.92919921875, 2.33642578125, 3, 0.824176262726], - [-0.69677734375, 5.26611328125, 2, -3.07712269694], - [-0.69677734375, 5.26611328125, 3, 16.2727733468], - [-1.18505859375, 0.94482421875, 2, 2.77814715345], - [-0.40869140625, 1.36962890625, 2, -0.0856869867897], - [-0.40869140625, 1.36962890625, 3, 3.83000877245], - [0.47998046875, 2.36572265625, 2, -3.87362577074], - [0.47998046875, 2.36572265625, 3, 7.18911882231], - [2.43310546875, 14.9340820313, 2, -22.5779082973], - [2.43310546875, 14.9340820313, 3, 1.30824813969] + [[1.002441406, 7.507324219, 0, -10.65658678], + [1.002441406, 7.507324219, 1, 20.11144222], + [-1.497558594, 7.507324219, 0, -2.802605142], + [-1.497558594, 7.507324219, 1, 7.894915287], + [-0.2475585938, 3.757324219, 0, -2.979595959], + [-0.2475585938, 3.757324219, 1, 14.42443563], + [3.497558594, 7.492675781, 0, -18.48058016], + [3.497558594, 7.492675781, 1, -90.76333962], + [3.497558594, 7.492675781, 2, -21.37443044], + [2.247558594, 3.742675781, 0, -10.80358935], + [2.247558594, 3.742675781, 1, -34.88579727], + [2.247558594, 3.742675781, 2, -23.29208387], + [2.252441406, 0.00732421875, 0, -7.083577593], + [2.252441406, 0.00732421875, 1, -50.04406495], + [2.252441406, 0.00732421875, 2, -18.17545536], + [2.252441406, 11.25732422, 0, -18.33357759], + [2.252441406, 11.25732422, 1, -5.044064945], + [2.252441406, 11.25732422, 2, -117.7565985], + [1.002441406, 11.25732422, 0, -14.40658678], + [1.002441406, 11.25732422, 1, 35.11144222], + [-0.2475585938, 0.00732421875, 0, 0.7704040407], + [1.627441406, 13.13232422, 0, -18.24508218], + [1.627441406, 13.13232422, 1, 26.38900286], + [-0.8725585938, 1.882324219, 0, 0.8588994492], + [-0.3842773438, 11.69677734, 0, -10.48953446], + [-0.3842773438, 11.69677734, 1, 45.329674], + [0.3774414062, 1.882324219, 0, -3.068091368], + [0.3774414062, 1.882324219, 1, 6.123253143], + [2.247558594, 13.11767578, 0, -20.17858935], + [2.247558594, 13.11767578, 1, 2.614202729], + [0.3774414062, 0.00732421875, 0, -1.193091368], + [0.3774414062, 0.00732421875, 1, -1.376746857], + [0.3774414062, 0.00732421875, 2, -31.98571425], + [-1.497558594, 1.882324219, 0, 2.822394858], + [1.935058594, 12.18017578, 0, -18.25934164], + [1.935058594, 12.18017578, 1, 11.76444554], + [-0.3256835938, 7.434082031, 0, -6.410916846], + [-0.3256835938, 7.434082031, 1, 28.68946113], + [1.939941406, 11.25732422, 0, -17.35182989], + [1.939941406, 11.25732422, 1, 7.88629751], + [-1.204589844, 9.484863281, 0, -5.700532678], + [-1.204589844, 9.484863281, 1, 23.61829501], + [2.096191406, 11.72607422, 0, -18.31145374], + [2.096191406, 11.72607422, 1, 3.537073421], + [2.945800781, 14.21630859, 0, -23.47081469], + [2.945800781, 14.21630859, 1, -28.78064866], + [2.945800781, 14.21630859, 2, -141.699449], + [2.437988281, 13.92333984, 0, -21.58250592], + [2.437988281, 13.92333984, 1, -2.969465573], + [2.437988281, 13.92333984, 2, -168.9838774], + [-0.5161132812, 9.045410156, 0, -7.423992463], + [-0.5161132812, 9.045410156, 1, 33.55264529], + [-1.043457031, 5.075683594, 0, -1.79756665], + [-1.043457031, 5.075683594, 1, 9.556683678], + [-0.2524414062, 1.853027344, 0, -1.059959276], + [-0.2524414062, 1.853027344, 1, 6.783152416], + [-0.5551757812, 2.819824219, 0, -1.075688063], + [-0.5551757812, 2.819824219, 1, 8.237285945], + [-0.5649414062, 0.9155273438, 0, 0.8592884278], + [-0.5698242188, 1.853027344, 0, -0.06287176429], + [-0.5698242188, 1.853027344, 1, 4.207452376] ], dtype=np.double) diff --git a/test/problems/test_GKLS.py b/test/problems/test_GKLS.py deleted file mode 100644 index 7fe9ea2..0000000 --- a/test/problems/test_GKLS.py +++ /dev/null @@ -1,30 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.GKLS import GKLS -import test.problems.pointsForTest.gkls_points as Sample - - -class TestGKLS(unittest.TestCase): - """setUp method is overridden from the parent class GKLS""" - - def setUp(self): - self.problem = GKLS(3, 1) - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][self.problem.dimension], 5) - - def test_OptimumValue(self): - self.assertEqual(self.problem.known_optimum[0].function_values[0].value, -1.0) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_all_problems.py b/test/problems/test_all_problems.py new file mode 100644 index 0000000..6a3ea66 --- /dev/null +++ b/test/problems/test_all_problems.py @@ -0,0 +1,192 @@ +import unittest +import numpy as np +from iOpt.trial import FunctionValue +from iOpt.trial import FunctionType +from iOpt.trial import Point + + +from problems.ex1222 import ex1222 +from problems.Floudas import Floudas +from problems.g8c import g8c +from problems.gbd import gbd +from problems.GKLS import GKLS +from problems.grishagin import Grishagin +from problems.nvs21 import nvs21 +from problems.p1 import p1 +from problems.p2 import p2 +from problems.p7 import p7 +from problems.Pern import Pern +from problems.rastrigin import Rastrigin +from problems.rastriginInt import RastriginInt +from problems.romeijn1c import Romeijn1c +from problems.romeijn2c import Romeijn2c +from problems.romeijn3c import Romeijn3c +from problems.romeijn5c import Romeijn5c +from problems.stronginc2 import Stronginc2 +from problems.stronginc3 import Stronginc3 +from problems.stronginc5 import Stronginc5 +from problems.shekel4 import Shekel4 +from problems.Synthes import Synthes +from problems.Yuan import Yuan + + + +import test.problems.pointsForTest as pft +from test.problems.pointsForTest import ex1222_points, Floudas_points, g8c_points, gbd_points, gkls_points, grishagin_points,\ + nvs21_points, p1_points, p2_points, p7_points, \ + Pern_points, rastrigin_points, rastriginInt_points, romeijn1c_points, romeijn2c_points, romeijn3c_points, \ + romeijn5с_points, stronginc2_points, stronginc3_points, stronginc5_points, \ + shekel4_points, Synthes_points, Yuan_points + + +class TestAllProblems(unittest.TestCase): + + def test_ex1222(self): + problem = ex1222() + sample = pft.ex1222_points + self.Calculate(problem, sample) + + def test_Floudas(self): + problem = Floudas() + sample = pft.Floudas_points + self.Calculate(problem, sample) + + def test_g8c(self): + problem = g8c() + sample = pft.g8c_points + self.Calculate(problem, sample) + + def test_gbd(self): + problem = gbd() + sample = pft.gbd_points + self.Calculate(problem, sample) + + def test_GKLS(self): + problem = GKLS(3,1) + sample = pft.gkls_points + self.Calculate(problem, sample) + + def test_Grishagin(self): + problem = Grishagin(1) + sample = pft.grishagin_points + self.Calculate(problem, sample) + + def test_nvs21(self): + problem = nvs21() + sample = pft.nvs21_points + self.Calculate(problem, sample) + + def test_p1(self): + problem = p1() + sample = pft.p1_points + self.Calculate(problem, sample) + + def test_p2(self): + problem = p2() + sample = pft.p2_points + self.Calculate(problem, sample) + + def test_p7(self): + problem = p7() + sample = pft.p7_points + self.Calculate(problem, sample) + + def test_Pern(self): + problem = Pern() + sample = pft.Pern_points + self.Calculate(problem, sample) + + def test_Rastrigin(self): + problem = Rastrigin(2) + sample = pft.rastrigin_points + self.Calculate(problem, sample) + + def test_RastriginInt(self): + problem = RastriginInt(3, 2) + sample = pft.rastriginInt_points + self.Calculate(problem, sample) + + def test_Romeijn1c(self): + problem = Romeijn1c() + sample = pft.romeijn1c_points + self.Calculate(problem, sample) + + def test_Romeijn2c(self): + problem = Romeijn2c() + sample = pft.romeijn2c_points + self.Calculate(problem, sample) + + def test_Romeijn3c(self): + problem = Romeijn3c() + sample = pft.romeijn3c_points + self.Calculate(problem, sample) + + def test_Romeijn5c(self): + problem = Romeijn5c() + sample = pft.romeijn5с_points + self.Calculate(problem, sample) + + def test_Stronginc2(self): + problem = Stronginc2() + sample = pft.stronginc2_points + self.Calculate(problem, sample) + + def test_Stronginc3(self): + problem = Stronginc3() + sample = pft.stronginc3_points + self.Calculate(problem, sample) + + def test_Stronginc5(self): + problem = Stronginc5() + sample = pft.stronginc5_points + self.Calculate(problem, sample) + + def test_Shekel4(self): + problem = Shekel4(1) + sample = pft.shekel4_points + self.Calculate(problem, sample) + + def test_Synthes(self): + problem = Synthes() + sample = pft.Synthes_points + self.Calculate(problem, sample) + + def test_Yuan(self): + problem = Yuan() + sample = pft.Yuan_points + self.Calculate(problem, sample) + + def Calculate(self, problem, Sample): + for i in range(0, len(Sample.test_points)): + fv_point = [] + for j in range(0, problem.number_of_float_variables): + fv_point.append(np.double(Sample.test_points[i][j])) + dv_point = [] + for j in range(problem.number_of_float_variables, problem.dimension): + dv_point.append(Sample.test_points[i][j]) + + point = Point(fv_point, dv_point) + function_value = FunctionValue() + + if problem.number_of_constraints > 0: + if Sample.test_points[i][problem.dimension] == problem.number_of_constraints: + function_value.type = FunctionType.OBJECTIV + else: + function_value.type = FunctionType.CONSTRAINT + function_value.functionID = Sample.test_points[i][problem.dimension] + + function_value = problem.calculate(point, function_value) + + if problem.number_of_constraints > 0: + self.assertAlmostEqual(function_value.value, + np.double(Sample.test_points[i][problem.dimension+1]), 5) + else: + self.assertAlmostEqual(function_value.value, + np.double(Sample.test_points[i][problem.dimension]), 5) + + print(problem.name, "is OK") + + +"""Executing the tests in the above test case class""" +if __name__ == "__main__": + unittest.main() diff --git a/test/problems/test_g8c_problem.py b/test/problems/test_g8c_problem.py deleted file mode 100644 index ca01bc8..0000000 --- a/test/problems/test_g8c_problem.py +++ /dev/null @@ -1,30 +0,0 @@ -import unittest -from iOpt.trial import FunctionValue -from iOpt.trial import FunctionType -from iOpt.trial import Point -from problems.g8c import g8c -import test.problems.pointsForTest.g8c_points as Sample - -class Testg8c(unittest.TestCase): - """setUp method is overridden from the parent class g8c""" - - def setUp(self): - self.problem = g8c() - - def test_CalculateAll(self): - for i in range(3, 99): - point = Point([Sample.test_points[i][0], Sample.test_points[i][1]], []) - functionValue = FunctionValue() - if Sample.test_points[i][2] == -1: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][2] - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][3], 6) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_grishagin_problem.py b/test/problems/test_grishagin_problem.py deleted file mode 100644 index 9c250c3..0000000 --- a/test/problems/test_grishagin_problem.py +++ /dev/null @@ -1,27 +0,0 @@ -import unittest -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.grishagin import Grishagin -import test.problems.pointsForTest.grishagin_points as Sample - - -class TesGrishagin(unittest.TestCase): - """setUp method is overridden from the parent class Grishagin""" - - def setUp(self): - self.problem = Grishagin(1) - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([Sample.test_points[i][0], Sample.test_points[i][1]], []) - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][2], 7) - - def test_OptimumValue(self): - self.assertEqual(self.problem.known_optimum[0].function_values[0].value, -13.514478495433776) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_rastriginInt_problem.py b/test/problems/test_rastriginInt_problem.py deleted file mode 100644 index 2b1ecbf..0000000 --- a/test/problems/test_rastriginInt_problem.py +++ /dev/null @@ -1,26 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.rastriginInt import RastriginInt -import test.problems.pointsForTest.rastriginInt_points as Sample - - -class TestRastriginInt(unittest.TestCase): - """setUp method is overridden from the parent class Rastrigin""" - - def setUp(self): - self.problem = RastriginInt(3, 2) - - def test_CalculateAll(self): - for i in range(0, 80): - point = Point([np.double(Sample.test_points[i][0])], [Sample.test_points[i][1], Sample.test_points[i][2]]) - - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, np.double(Sample.test_points[i][3]), 6) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_rastrigin_problem.py b/test/problems/test_rastrigin_problem.py deleted file mode 100644 index 7d69c85..0000000 --- a/test/problems/test_rastrigin_problem.py +++ /dev/null @@ -1,27 +0,0 @@ -import unittest -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.rastrigin import Rastrigin -import test.problems.pointsForTest.rastrigin_points as Sample - - -class TestRastrigin(unittest.TestCase): - """setUp method is overridden from the parent class Rastrigin""" - - def setUp(self): - self.problem = Rastrigin(2) - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([Sample.test_points[i][0], Sample.test_points[i][1]], []) - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][2], 7) - - def test_OptimumValue(self): - self.assertEqual(self.problem.known_optimum[0].function_values[0].value, 0.0) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_romeijn1c_problem.py b/test/problems/test_romeijn1c_problem.py deleted file mode 100644 index 11ab161..0000000 --- a/test/problems/test_romeijn1c_problem.py +++ /dev/null @@ -1,37 +0,0 @@ -import unittest - -import numpy as np - -import test.problems.pointsForTest.romeijn1c_points as Sample -from iOpt.trial import FunctionType -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.romeijn1c import Romeijn1c - - -class TestRomeijn1c(unittest.TestCase): - """setUp method is overridden from the parent class Romeijn1c""" - - def setUp(self): - self.problem = Romeijn1c() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - if Sample.test_points[i][self.problem.dimension] == 1: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][self.problem.dimension] - 2 - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][self.problem.dimension+1], 6) - - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_romeijn2c_problem.py b/test/problems/test_romeijn2c_problem.py deleted file mode 100644 index f697e6e..0000000 --- a/test/problems/test_romeijn2c_problem.py +++ /dev/null @@ -1,34 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.romeijn2c import Romeijn2c -from iOpt.trial import FunctionType -import test.problems.pointsForTest.romeijn2c_points as Sample - - -class TestRomeijn2c(unittest.TestCase): - """setUp method is overridden from the parent class RomeijnC2""" - - def setUp(self): - self.problem = Romeijn2c() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - if Sample.test_points[i][6] == 1: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][self.problem.dimension]-2 - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][7], 7) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_romeijn3c_problem.py b/test/problems/test_romeijn3c_problem.py deleted file mode 100644 index 906ffee..0000000 --- a/test/problems/test_romeijn3c_problem.py +++ /dev/null @@ -1,34 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.romeijn3c import Romeijn3c -from iOpt.trial import FunctionType -import test.problems.pointsForTest.romeijn3c_points as Sample - - -class TestRomeijn3c(unittest.TestCase): - """setUp method is overridden from the parent class Romeijn3c""" - - def setUp(self): - self.problem = Romeijn3c() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - if Sample.test_points[i][self.problem.dimension] == 1: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][self.problem.dimension]-2 - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][self.problem.dimension+1], 7) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git "a/test/problems/test_romeijn5\321\201_problem.py" "b/test/problems/test_romeijn5\321\201_problem.py" deleted file mode 100644 index 9f6a5aa..0000000 --- "a/test/problems/test_romeijn5\321\201_problem.py" +++ /dev/null @@ -1,35 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.romeijn5c import Romeijn5c -from iOpt.trial import FunctionType -import test.problems.pointsForTest.romeijn5с_points as Sample - - -class TestRomeijn5c(unittest.TestCase): - """setUp method is overridden from the parent class Romeijn5c""" - - def setUp(self): - self.problem = Romeijn5c() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - if Sample.test_points[i][self.problem.dimension] == 1: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][self.problem.dimension] - 2 - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][self.problem.dimension + 1], 7) - - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_shekel4_problem.py b/test/problems/test_shekel4_problem.py deleted file mode 100644 index 25a46ed..0000000 --- a/test/problems/test_shekel4_problem.py +++ /dev/null @@ -1,36 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.shekel4 import Shekel4 -import test.problems.pointsForTest.shekel4_points as Sample - - -class TestShekel4(unittest.TestCase): - """setUp method is overridden from the parent class Shekel4""" - - def setUp(self): - self.fn = 1 - self.problem = Shekel4(self.fn) - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][self.problem.dimension], 7) - - def test_OptimumValue(self): - pointfv = np.ndarray(shape=(self.problem.dimension), dtype=np.double) - pointfv.fill(4) - point = Point(pointfv, []) - functionValue = FunctionValue() - functionValue = self.problem.calculate(point, functionValue) - self.assertEqual(self.problem.known_optimum[0].function_values[0].value, functionValue.value) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_stronginc2_problem.py b/test/problems/test_stronginc2_problem.py deleted file mode 100644 index fbc321a..0000000 --- a/test/problems/test_stronginc2_problem.py +++ /dev/null @@ -1,31 +0,0 @@ -import unittest -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.stronginc2 import Stronginc2 -from iOpt.trial import FunctionType -import test.problems.pointsForTest.stronginc2_points as Sample - - -class TestStronginc2(unittest.TestCase): - """setUp method is overridden from the parent class Stronginc2""" - - def setUp(self): - self.problem = Stronginc2() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([Sample.test_points[i][0], Sample.test_points[i][1]], []) - functionValue = FunctionValue() - if Sample.test_points[i][2] == 2: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][2] - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][3], 6) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_stronginc3_problem.py b/test/problems/test_stronginc3_problem.py deleted file mode 100644 index 1cf6abf..0000000 --- a/test/problems/test_stronginc3_problem.py +++ /dev/null @@ -1,33 +0,0 @@ -import unittest - -import test.problems.pointsForTest.stronginc3_points as Sample -from iOpt.trial import FunctionType -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.stronginc3 import Stronginc3 - - -class TestStronginc3(unittest.TestCase): - """setUp method is overridden from the parent class Stronginc3""" - - def setUp(self): - self.problem = Stronginc3() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([Sample.test_points[i][0], Sample.test_points[i][1]], []) - functionValue = FunctionValue() - if Sample.test_points[i][2] == 3: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][2] - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][3], 6) - - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() diff --git a/test/problems/test_stronginc5_problem.py b/test/problems/test_stronginc5_problem.py deleted file mode 100644 index 86d9863..0000000 --- a/test/problems/test_stronginc5_problem.py +++ /dev/null @@ -1,35 +0,0 @@ -import unittest -import numpy as np -from iOpt.trial import FunctionValue -from iOpt.trial import Point -from problems.stronginc5 import Stronginc5 -from iOpt.trial import FunctionType -import test.problems.pointsForTest.stronginc5_points as Sample - - -class TestStronginc5(unittest.TestCase): - """setUp method is overridden from the parent class Stronginc5""" - - def setUp(self): - self.problem = Stronginc5() - - def test_CalculateAll(self): - for i in range(0, 99): - point = Point([], []) - for j in range(0, self.problem.dimension): - point.float_variables = np.append(point.float_variables, Sample.test_points[i][j]) - functionValue = FunctionValue() - if Sample.test_points[i][5] == 5: - functionValue.type = FunctionType.OBJECTIV - else: - functionValue.type = FunctionType.CONSTRAINT - functionValue.functionID = Sample.test_points[i][5] - - functionValue = self.problem.calculate(point, functionValue) - self.assertAlmostEqual(functionValue.value, Sample.test_points[i][6], 6) - - -"""Executing the tests in the above test case class""" -if __name__ == "__main__": - unittest.main() -