for idx_msmt_var in Multiples:
unique_id = path + 'tg_' + prefix + fname_likelihood + '_m_' + str(
idx_msmt_var)
GLOBALDICT["MODELDESIGN"]["MAX_NUM_ITERATIONS"] = len(
sensing_qubits) * idx_msmt_var
GLOBALDICT["MODELDESIGN"]["ID"] = unique_id
qslam_br = 0.
naive_br = 0.
qslamdata = 0.
naivedata = 0.
# print(GLOBALDICT["INTERPOLATE_FLAG"])
try:
qslam_br = riskqslam(copy.deepcopy(TRUTHKWARGS),
copy.deepcopy(GLOBALDICT))
naive_br = risknaive(copy.deepcopy(TRUTHKWARGS),
copy.deepcopy(GLOBALDICT))
qslam_br.naive_implementation(randomise='OFF')
naive_br.naive_implementation()
except:
print "Index: %s was not completed..." % (idx_msmt_var)
print "Error information:"
print "Type", sys.exc_info()[0]
print "Value", sys.exc_info()[1]
print "Traceback", traceback.format_exc()
idx_var_dict)
testcase_ID = regime_ID + '_t_' + str(idx_prevar) + '_m_' + str(
idx_msmt_var)
unique_id = savetopath + testcase_ID + '_v_' + str(idx_var)
vars()['vardict_' + str(idx_var_dict)]["MODELDESIGN"]["ID"] = unique_id
qslam_br = 0.
naive_br = 0.
qslamdata = 0.
naivedata = 0.
try:
qslam_br = riskqslam(vardict_truth,
vars()['vardict_' + str(idx_var_dict)])
naive_br = risknaive(vardict_truth,
vars()['vardict_' + str(idx_var_dict)])
qslam_br.naive_implementation(randomise='OFF')
naive_br.naive_implementation()
print "Variation | Set: %s | Index: %s successful..." % (
idx_var_dict, idx_var)
except:
print "Variation | Set: %s | Index: %s was not completed..." % (
idx_var_dict, idx_var)
print "Error information:"
print "Type", sys.exc_info()[0]
print "Value", sys.exc_info()[1]
print "Traceback", traceback.format_exc()