Coverage for robust\signomial_simple_wing\models.py : 0%

from gpkit import Variable, Model, SignomialsEnabled, units 

from robust.simulations import simulate, read_simulation_data 

import os 

from gpkitmodels.SP.SimPleAC.SimPleAC_mission import SimPleAC, Mission 

from gpkitmodels.SP.SimPleAC.SimPleAC import SimPleAC as simpleWingSP 

def example_sp(): 

x = Variable('x') 

y = Variable('y') 

a = Variable('a', 1, pr=10) 

b = Variable('b', 1, pr=10) 

constraints = [] 

with SignomialsEnabled(): 

constraints = constraints + [x >= 1 - a * y, b * y <= 0.1] 

return Model(x, constraints) 

def simple_wing_sp(): 

the_model = simpleWingSP() 

the_model.cost = the_model['W_f'] 

return the_model 

def simple_ac(): 

the_model = Mission(SimPleAC(), 4) 

the_model.substitutions.update({ 

'h_{cruise_m}': 5000 * units('m'), 

'Range_m': 3000 * units('km'), 

'W_{p_m}': 6250 * units('N'), 

'C_m': 120 * units('1/hr'), 

'V_{min_m}': 25 * units('m/s'), 

'T/O factor_m': 2, 

}) 

c = Variable('c', '-', 'model cost') 

the_model = Model(c, [the_model, c >= the_model['W_{f_m}'] * units('1/N') + the_model['C_m'] * the_model['t_m']]) 

return the_model 

if __name__ == '__main__': 

model = simple_ac() 

number_of_time_average_solves = 3 # 100 

number_of_iterations = 15 # 1000 

nominal_solution, nominal_solve_time, nominal_number_of_constraints, directly_uncertain_vars_subs = \ 

simulate.generate_model_properties(model, number_of_time_average_solves, number_of_iterations) 

model_name = 'Signomial Simple Flight' 

gammas = [0.6, 1] # [0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1] 

min_num_of_linear_sections = 3 

max_num_of_linear_sections = 99 

linearization_tolerance = 1e-3 

verbosity = 1 

methods = [{'name': 'Best Pairs', 'twoTerm': True, 'boyd': False, 'simpleModel': False}, 

{'name': 'Linearized Perturbations', 'twoTerm': False, 'boyd': False, 'simpleModel': False}, 

{'name': 'Simple Conservative', 'twoTerm': False, 'boyd': False, 'simpleModel': True}] 

uncertainty_sets = ['box', 'elliptical'] 

model = simple_ac() 

variable_gamma_file_name = os.path.dirname(__file__) + '/simulation_data_variable_gamma.txt' 

simulate.print_variable_gamma_results(model, model_name, gammas, number_of_iterations, 

min_num_of_linear_sections, 

max_num_of_linear_sections, verbosity, linearization_tolerance, 

variable_gamma_file_name, number_of_time_average_solves, methods, 

uncertainty_sets, nominal_solution, nominal_solve_time, 

nominal_number_of_constraints, directly_uncertain_vars_subs) 

gamma = 1 

numbers_of_linear_sections = [40, 60] # [12, 14, 15, 16, 17, 18, 20, 22, 24, 26, 28, 30, 32, 36, 44, 52, 60, 70, 80] 

methods = [{'name': 'Best Pairs', 'twoTerm': True, 'boyd': False, 'simpleModel': False}, 

{'name': 'Linearized Perturbations', 'twoTerm': False, 'boyd': False, 'simpleModel': False}] 

uncertainty_sets = ['box', 'elliptical'] 

variable_pwl_file_name = os.path.dirname(__file__) + '/simulation_data_variable_pwl.txt' 

simulate.print_variable_pwlsections_results(model, model_name, gamma, number_of_iterations, 

numbers_of_linear_sections, linearization_tolerance, 

verbosity, variable_pwl_file_name, 

number_of_time_average_solves, methods, uncertainty_sets, 

nominal_solution, nominal_solve_time, 

nominal_number_of_constraints, 

directly_uncertain_vars_subs) 

file_path_gamma = os.path.dirname(__file__) + '/simulation_data_variable_gamma.txt' 

file_path_pwl = os.path.dirname(__file__) + '/simulation_data_variable_pwl.txt' 

read_simulation_data.generate_all_plots(file_path_gamma, file_path_pwl)