def third_task():
implicit_limit1 = InequationLimit(lambda x, y: y - x)
implicit_limit2 = InequationLimit(lambda x, y: 2 - x)
explicit_limit1 = LowerLimit([-100, -100])
explicit_limit2 = UpperLimit([100, 100])
print_headers('BOX', '$' * 20)
print_headers('First function', '-' * 10)
func, start_point = get_function_and_start_point(1)
securely_call_function_and_print_result(box,
func,
start_point,
[implicit_limit1, implicit_limit2],
[explicit_limit1, explicit_limit2],
enable_output=True)
# result = box(func, start_point, [implicit_limit1, implicit_limit2], [explicit_limit1, explicit_limit2], enable_output=True)
# print_result(result, func)
print_headers('Second function', '-' * 10)
func, start_point = get_function_and_start_point(2)
securely_call_function_and_print_result(box,
func,
start_point,
[implicit_limit1, implicit_limit2],
[explicit_limit1, explicit_limit2],
enable_output=True)
def first_task_golden():
print_headers('Using golden step', '-' * 10)
func, start_point = get_function_and_start_point(3)
securely_call_function_and_print_result(gradient,
func,
start_point,
shift_type='golden',
enable_output=PRINT_STEPS)
def second_task():
print_headers('GRADIENT', '$' * 20)
print_headers('First function', '-' * 10)
func, start_point = get_function_and_start_point(1)
securely_call_function_and_print_result(gradient,
func,
start_point,
shift_type='golden',
enable_output=PRINT_STEPS)
# result = gradient(func, start_point, shift_type='golden', enable_output=PRINT_STEPS)
# print_result(result, func)
print_headers('Second function', '-' * 10)
func, start_point = get_function_and_start_point(2)
securely_call_function_and_print_result(gradient,
func,
start_point,
shift_type='golden',
enable_output=PRINT_STEPS)
# result = gradient(func, start_point, shift_type='golden', enable_output=PRINT_STEPS)
# print_result(result, func)
print_headers('NEWTON-RAPHSON', '$' * 20)
print_headers('First function', '-' * 10)
func, start_point = get_function_and_start_point(1)
securely_call_function_and_print_result(newton_raphson,
func,
start_point,
shift_type='golden',
enable_output=PRINT_STEPS)
# result = newton_raphson(func, start_point, shift_type='golden', enable_output=PRINT_STEPS)
# print_result(result, func)
print_headers('Second function', '-' * 10)
func, start_point = get_function_and_start_point(2)
securely_call_function_and_print_result(newton_raphson,
func,
start_point,
shift_type='golden',
enable_output=PRINT_STEPS)
def fifth_task():
implicit_limit1 = InequationLimit(lambda x, y: 3 - x - y)
implicit_limit2 = InequationLimit(lambda x, y: 3 + 1.5 * x - y)
implicit_limit3 = EquationLimit(lambda x, y: y - 1)
func, _ = get_function_and_start_point(4)
start_point = (5, 5)
securely_call_function_and_print_result(
transformation,
func,
start_point, [implicit_limit1, implicit_limit2, implicit_limit3],
enable_output=True)
def fourth_task():
implicit_limit1 = InequationLimit(lambda x, y: y - x)
implicit_limit2 = InequationLimit(lambda x, y: 2 - x)
print_headers('First function', '-' * 10)
func, start_point = get_function_and_start_point(1)
securely_call_function_and_print_result(transformation,
func,
start_point,
[implicit_limit1, implicit_limit2],
enable_output=True)
# result = transformation(func, start_point, [implicit_limit1, implicit_limit2], enable_output=True)
# print_result(result, func)
print_headers('Second function', '-' * 10)
func, start_point = get_function_and_start_point(2)
securely_call_function_and_print_result(transformation,
func,
start_point,
[implicit_limit1, implicit_limit2],
enable_output=True)
if enable_output:
print(output)
raise ArithmeticError('It exceeded maximum nr of iterations')
total_iterations += 1
if enable_output:
print(output)
return current_point
def calculate_shift_for_classic(gradient):
shift = deepcopy(gradient)
shift = multiply_each_element(shift, -1)
return shift
def calculate_shift_for_golden(function, current_point, gradient):
lambda_function = LambdaFunction(function, current_point, gradient)
return multiply_each_element(
gradient,
golden_section.find_function_min(lambda_function, start_point=0))
if __name__ == '__main__':
print(
find_function_min(*get_function_and_start_point(3),
shift_type='golden',
enable_output=True))
def first_task():
print_headers('Using whole gradient step', '-' * 10)
securely_call_function_and_print_result(gradient,
*get_function_and_start_point(3),
enable_output=False)