if res.success and res.fun < 1.0e-5 and volfrac <= 1.0:
return comp_mf(cas, BOB, spids, propvec, volfrac), volfrac
else:
eff = comp_mf(cas, BOB, spids, propvec, 1.0)
return eff, 1.0
if __name__ == '__main__':
print("=================================================================")
print("Finding blend levels for fixed efficiency")
print("=================================================================")
matplotlib.rc('xtick', labelsize=24)
matplotlib.rc('ytick', labelsize=24)
matplotlib.rc('axes', titlesize=24)
matplotlib.rc('font', size=24)
propDB = load_propDB('testDB.xls')
ncomp, spids, propvec = make_property_vector_all(propDB)
# Volume fractions:
wb = xlrd.open_workbook('test_list.xlsx')
ws = wb.sheet_by_index(0)
cas_list = []
nm_list = []
jbm_list = []
cas_col = ws.col(0)
for c, jb, nm in zip(cas_col[1:], ws.col(2)[1:], ws.col(1)[1:]):
cas_list.append(c.value)
jbm_list.append(jb.value)
nm_list.append(nm.value)
if True:
f.write("{}\t".format(c[h]))
f.write("\n")
if __name__ == '__main__':
t0 = time.time()
print("=================================================================")
print("Welcome to the Co-optimizer")
print("=================================================================")
print('-----------------------------------------------------------------')
print("Setting up:")
print("Reading fuel component properties from: ",
cooptimizer_input.component_properties_database)
propDB = load_propDB(cooptimizer_input.component_properties_database,
maxrows=18, maxcols=14)
print("Reading fuel component costs from: ",
cooptimizer_input.component_cost_database)
propDB = load_propDB(cooptimizer_input.component_cost_database,
propDB_initial=propDB, maxrows=18, maxcols=3)
print('-----------------------------------------------------------------')
output_files = []
for t, v in cooptimizer_input.task_list.items():
if v:
ans = 'Yes'
else:
ans = 'No'
print('Planning to perform task: ', t, '\t\t', ans)
if k in comp.keys():
ws.write(j, i, comp[k])
i += 1
j += 1
wb.save(output_file)
if __name__ == '__main__':
cas = read_input_list('assert_20.xls')
# Add blendstocks to this as well as flag for is it a blend so that
# know how to map it to fpdatabase fields
print("{}".format(cas))
keys = ['Pure_CAS', 'pk_UUID', 'Pure_Molecular_Formula', 'Pure_IUPAC_name',
'Pure_Molecular_Weight', 'Pure_Boiling_Point',
'Pure_LHV', 'Pure_Heat_of_Vaporization',
'Pure_RON', 'Pure_MON', 'Pure_PMI', 'Pure_Density',
'Blend_Name', 'Blend_Density', 'Blend_HoV', 'Blend_LHV',
'Blend_MON', 'Blend_RON', 'Blend_PMI']
data = load_raw_fpdatabase('Fuel Engine Co Optimization-2.csv', cas, keys)
write_propDB_remap('testpropDB.xls', data)
# Now re-read that file, combine with the bRON data and write
# out the result:
propDB = load_propDB('testpropDB.xls')
propDB = load_propDB('bRON_data_with_CAS.xls', propDB_initial=propDB)
write_propDB('testDB.xls', propDB)