def main():
params, results = di.read_parameters_file()
rosen_input = pack_rosen_parameters(params, results)
rosen_output = rosenbrock_list(**rosen_input)
results = pack_dakota_results(rosen_output, results)
results.write()
# Alternatively, the ASV can be accessed by index in
# function, gradient, hessian order
#for i, bit in enumerate(results["obj_fn"].asv):
# if bit:
# active_set_vector += 1 << i
# set a dictionary for passing to rosenbrock via Python kwargs
rosen_params = {}
rosen_params['cv'] = continuous_vars
rosen_params['asv'] = [active_set_vector]
rosen_params['functions'] = 1
# execute the rosenbrock analysis as a separate Python module
print "Running rosenbrock..."
from rosenbrock import rosenbrock_list
rosen_results = rosenbrock_list(**rosen_params)
print "Rosenbrock complete."
# ----------------------------
# Return the results to Dakota
# ----------------------------
# Insert functions from rosen into results
# Results iterator provides an index, response name, and response
for i, n, r in results:
if r.asv.function:
r.function = rosen_results['fns'][i]
if r.asv.gradient:
r.gradient = rosen_results['fnGrads'][i]
if r.asv.hessian:
r.hessian = rosen_results['fnHessians'][i]
# set up the data structures the rosenbrock analysis code expects
# for this simple example, put all the variables into a single hardwired array
continuous_vars = [ float(paramsdict['x1']), float(paramsdict['x2']) ]
active_set_vector = [ int(paramsdict['ASV_1:obj_fn']) ]
# set a dictionary for passing to rosenbrock via Python kwargs
rosen_params = {}
rosen_params['cv'] = continuous_vars
rosen_params['asv'] = active_set_vector
rosen_params['functions'] = 1
# execute the rosenbrock analysis as a separate Python module
print "Running rosenbrock..."
from rosenbrock import rosenbrock_list
rosen_results = rosenbrock_list(**rosen_params)
print "Rosenbrock complete."
# ----------------------------
# Return the results to DAKOTA
# ----------------------------
# write the results.out file for return to DAKOTA
# this example only has a single function, so make some assumptions;
# not processing DVV
outfile = open('results.out.tmp', 'w')
# write functions
for func_ind in range(0, num_fns):
if (active_set_vector[func_ind] & 1):