self.linear_solver = om.DirectSolver()
if __name__ == "__main__":
# test script for trivial optimization to maximize battery temperature
from Conductors import parse_cond
from ViewFactors import parse_vf
from inits import inits
# define boundary conditions
nodals = 'Nodal_data.csv'
conductors = 'Cond_data.csv'
n, GL_init, GR_init, QI_init, QS_init = inits(nodals, conductors)
user_conductors = 'conductors.txt'
cond_data = parse_cond(user_conductors)
cond_nodes = {}
shape_factors = {}
k = {}
for entry in cond_data:
cond_nodes.update( {entry['cond_name'] : entry['nodes']} )
shape_factors.update( {entry['cond_name'] : entry['SF'] } )
k.update( {entry['cond_name'] : entry['conductivity'] } )
view_factors = 'viewfactors.txt'
vf_data = parse_vf(view_factors)
vf_nodes = []
area = []
params.add_output('beta', val=np.zeros(npts) )
params.add_output('dist', val=[1., 3.])
model = Solar(npts=npts, area=area)
model.add_subsystem('params', params, promotes=['*'])
problem = om.Problem(model=model)
problem.setup(check=True)
problem.run_model()
#check_partials_data = problem.check_partials(compact_print=True, show_only_incorrect=False, form='central', step=1e-02)
#compare results with esatan
nodes = 'Nodal_data.csv'
conductors = 'Cond_data.csv'
n, GL_init1, GR_init1, QI_init1, QS_init1 = inits(nodes, conductors)
nodes2 = 'Nodal_data_2.csv'
conductors2 = 'Cond_data_2.csv'
n, GL_init2, GR_init2, QI_init2, QS_init2 = inits(nodes2, conductors2)
npts = 2
QS_init = np.concatenate((QS_init2, QS_init1), axis=1)
print((problem['QS_c'] - QS_init[1:12,:]*0.91/0.61)/problem['QS_c'])
#print(QS_init[1:12,:]*0.91/0.61)
#problem.model.list_inputs(print_arrays=True)