def test_validation_parameters_false_9(self):
"""
if not are_subarray_len_valid(p.degree_smoothness, l):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1.5, 1], [0, -1]], [0, 1], [[-2, 1], [7.9]], [[1.4, 1], [0.1, 3]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_5(self):
"""
if not type_valid(p.function_values, [int, float]):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1, 1], [1, 1]], ['0', 1], [[1, 1], [1, 1]], [[1, 1], [1, 1]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_14(self):
"""
if func_type not in ["method_min", "hyperbolic_potential", "exponential_potential"]:
return False
"""
p = Parameters(1, "exponential_potential", 2, [[1.5, 1], [0, -1]], [0, 1],
[[-2, 1], [7.9, 0]], [1.4, 1], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "qwerty"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_11(self):
"""
if not are_subarray_len_valid(p.coefficients_abruptness, l):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1.5, 1], [0, -1]], [0, 1],
[[-2, 1], [7.9, 0]], [[1.4, 7], [0.1, 1.1, 0, 6]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_8(self):
"""
l = len(p.coordinates[0])
if not are_subarray_len_valid(p.coordinates, l):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1.5, 1], [0, -1, 0]], [0, 1], [[1, 1], [1, 1]], [[1.4, 1], [0.1, 3]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_1(self):
"""
n = p.number_extrema
if n < 1:
return False
"""
p = Parameters(1, "feldbaum_function", 0, [], [0, 1], [], [], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_12(self):
"""
if (func_type == "hyperbolic_potential") or (func_type == "exponential_potential"):
if not are_positive_elem_valid(p.function_values):
return False
"""
p = Parameters(1, "hyperbolic_potential_abs", 2, [[1.5, 1], [0, -1]], [0, -1],
[[-2, 1], [7.9, 0]], [[1.4, 7], [0.1, 1.1]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "hyperbolic_potential_abs"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_true(self):
"""
if (func_type == "hyperbolic_potential") or (func_type == "exponential_potential"):
...
if not type_valid(p.coefficients_abruptness, [int, float]):
return False
"""
p = Parameters(1, "exponential_potential", 2, [[1.5, 1], [0, -1]], [0, 1],
[[-2, 1], [7.9, 0]], [1.4, 1], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "exponential_potential"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, True)
def test_validation_parameters_false_10(self):
"""
if func_type == "method_min":
for i in range(n):
if not type_valid(p.coefficients_abruptness[i], [int, float]):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1.5, 1], [0, -1]], [0, 1],
[[-2, 1], [7.9, 0]], [[1.4, '6'], [0.1, 'dfg']], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_7(self):
"""
for i in range(n):
if not type_valid(p.coordinates[i], [int, float]):
return False # выход
if not type_valid(p.degree_smoothness[i], [int, float]):
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1.5, 1], ['0', 'h']], [0, 1], [[1, 1], [1, 1]], [[1.4, 1], [0.1, 3]], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def test_validation_parameters_false_4(self):
"""
ok = (n == len(p.coordinates)) and \ # истино
(n == len(p.function_values)) and \ # истино
(n == len(p.degree_smoothness)) and \ # истино
(n == len(p.coefficients_abruptness)) # ложно
if not ok:
return False
"""
p = Parameters(1, "feldbaum_function", 2, [[1, 1], [1, 1]], [0, 1], [0, 0], [1, 1, 1], [], [], [0,0], [1,1], min_f=0, max_f=1)
f_type = "feldbaum_function"
res = vld.validation_parameters(p, f_type)
self.assertEqual(res, False)
def read_parameters_function(self):
# TODO: добавить комментарии
self.idx_func, er = parser_field.parse_number(self.ui.idx_func.value(),
self.ui.idx_func_label)
if er != "":
self.display_error_message(er)
return
number_extrema, er = parser_field.parse_number(
self.ui.number_extrema.value(), self.ui.number_extrema_label)
if er != "":
self.display_error_message(er)
return
coordinates, er = parser_field.parse_coordinates(
self.ui.coordinates.text())
if er != "":
self.display_error_message(er)
return
function_values, er = parser_field.parse_field(
self.ui.function_values.text(),
self.ui.function_values_label.text())
if er != "":
self.display_error_message(er)
return
degree_smoothness, er = parser_field.parse_field(
self.ui.degree_smoothness.text(),
self.ui.degree_smoothness_label.text())
if er != "":
self.display_error_message(er)
return
coefficients, er = parser_field.parse_field(
self.ui.coefficients_abruptness_function.text(),
self.ui.coefficients_abruptness_function_label.text())
if er != "":
self.display_error_message(er)
return
func_type = self.read_type()
constraints_high, er = parser_field.parse_field(
self.ui.constraints_high.text(),
self.ui.constraints_x1_label.text())
if er != "":
self.display_error_message(er)
return
constraints_down, er = parser_field.parse_field(
self.ui.constraints_down.text(),
self.ui.constraints_x2_label.text())
if er != "":
self.display_error_message(er)
return
global_min, er = parser_field.parse_field(
self.ui.min_func_coord.text(), self.ui.min_label.text())
if er != "":
self.display_error_message(er)
return
global_max, er = parser_field.parse_field(
self.ui.max_func_coord.text(), self.ui.max_label.text())
if er != "":
self.display_error_message(er)
return
if len(global_min) != len(global_max) or len(global_min) != len(
coordinates[0]):
error = "Поля координат глобального минимума или максимума заполенны некорректно!"
self.display_error_message(error)
return None
if func_type != "":
p = Parameters(self.idx_func,
func_type,
number_extrema,
coordinates,
function_values,
degree_smoothness,
coefficients,
constraints_high,
constraints_down,
global_min,
global_max,
min_f=self.ui.min_func.value(),
max_f=self.ui.max_func.value())
ok = validation.validation_parameters(p, func_type)
if not ok:
error = "Одно или несколько полей заполнены некорректно!"
self.display_error_message(error)
return None
else:
return p