def CH4results():
choicesaveresults = raw_input("Save results? (y/n)")
results = []
for D_0 in CH4INLETS_VARY_D_0:
result = CCDroplet.main(gri30_gas,ctCH4,"methane",CH4_TUP,CH4CH_PARAMS,D_0,Hrefchoice='y', T_boilo=111.5)
results.append(result)
if choicesaveresults == 'y':
for result in results:
# sanity check
try:
Dsizestr = str(result['cleandat'].D[0]*10**6).split('.')[0]
except KeyError:
print "KeyError still! I'll print the type:"
print type(result)
filename = CH4_TUP.Fuelstr+str(CCDroplet.NUM_STEPS)+"steps"+"D"+Dsizestr+'v_d'+str(result['cleandat'].v_d[0]).split('.')[0]
tosave = pd.DataFrame(result['cleandat']._asdict(),index=result['xclean'])
# EY : 20160311 I wanted to implement hdf5 requiring PyTables but pip install
# of PyTables was nontrivial; received warning
# Warning! ***HDF5 library version mismatched error***
# Abort trap: 6
# would like to know best practices for serialization of pandas DataFrame
# try:
# tosave.to_hdf("./data/"+filename,filename)
# except:
# print "We're not in a directory where there's a subdirectory for data. Saving into working directory."
# try:
# tosave.to_hdf(filename,filename)
# except:
# print "PyTables may not be installed. Try pickle. Be careful of reading unknown pickles (see pandas doc for warning)"
try:
tosave.to_pickle("./data/"+filename+'.pkl')
except:
print "We're not in a directory where there's a subdirectory for data. Saving into working directory."
tosave.to_pickle(filename+'.pkl')
# (surjective) transforming from list of dicts, that includes raw data, to list of namedtuples of pandas dataframe, which only includes clean data
results = [pd.DataFrame(result['cleandat']._asdict(),index=result['xclean']) for result in results]
# D_0s = [int(str(result.D[0]*10**6).split('.')[0]) for result in results]
D_0s = [str(result.D[0]*10**6).split('.')[0] for result in results]
results = pd.concat(results,axis=1, keys=D_0s)
filename = CH4_TUP.Fuelstr+str(CCDroplet.NUM_STEPS)+"steps"+ str(results[D_0s[0]].v_d[0.0]).split('.')[0]
try:
results.to_pickle("./data/"+filename+'.pkl')
except:
print "We're not in a directory where there's a subdirectory for data. Saving into working directory."
results.to_pickle(filename+'.pkl')
return results
def output_from_main(gas,liquid,speciesname,reaction_tuple,chamber_params,inlet_conds,Hrefchoice,T_boilo):
"""
output_from_main(gas,liquid,speciesname,reaction_tuple,chamber_params,inlet_conds,T_boilo)
"""
choicesaveresults = raw_input("Save results? (y/n)")
results = []
for D_0 in inlet_conds:
result = CCDroplet.main(gas,liquid,speciesname,reaction_tuple,chamber_params,D_0,Hrefchoice, T_boilo)
results.append(result)
if choicesaveresults == 'y':
for result in results:
try:
Dsizestr = str(result['cleandat'].D[0]*10**6).split('.')[0]
except KeyError:
print "KeyError still! I'll print the type:"
print type(result)
filename = speciesname+"steps"+str(CCDroplet.NUM_STEPS)+"D"+Dsizestr+'v_d'+str(result['cleandat'].v_d[0]).split('.')[0]
tosave = pd.DataFrame(result['cleandat']._asdict(),index=result['xclean'])
try:
tosave.to_pickle("./data/"+filename)
except:
print "We're not in a directory where there's a subdirectory for data. Saving into working directory."
tosave.to_pickle(filename)
# (surjective) transforming from list of dicts, that includes raw data, to list of namedtuples of pandas dataframe, which only includes clean data
results = [pd.DataFrame(result['cleandat']._asdict(),index=result['xclean']) for result in results]
# D_0s = [int(str(result.D[0]*10**6).split(',')[0]) for result in results]
D_0s = [str(result.D[0]*10**6).split(',')[0] for result in results]
results = pd.concat(results,axis=1, keys=D_0s)
filename = speciesname+str(CCDroplet.NUM_STEPS)+"steps"+ str(results[D_0s[0]].v_d[0.0]).split('.')[0] +'v_d'
try:
results.to_pickle("./data/"+filename)
except:
print "We're not in a directory where there's a subdirectory for data. Saving into working directory."
results.to_pickle(filename)
return results
def CH4result(key):
"""
calculations for a single initial droplet size only
"""
result = CCDroplet.main(gri30_gas,ctCH4,"methane",CH4_TUP,CH4CH_PARAMS,CH4INLETS_VARY_D_0[key],Hrefchoice='y', Tboilo=111.5)
return result
def compute_flows_phi_g_v_g(gas,liquid,reaction_tuple,chamber_params,inlet_conds,T_boil,oderesults,Hrefchoice='y'):
"""
compute_flows_phi_g_v_g = compute_flows_phi_g_v_g(gas,liquid,reaction_tuple,T_boil,P,Hrefchoice)
oderesults - <CCDroplet.T_gDv_d_Tuple>
"""
P = inlet_conds.TP[1]
h_fg,T_boil,rho_l,h_l=CCDroplet._process_liquid_Droplet(gas,liquid,reaction_tuple,T_boil,P,Hrefchoice)
Fu_ind = gas.species_index(reaction_tuple.Fuelstr)
Ox_ind = gas.species_index(reaction_tuple.Oxstr)
gas.X = CCDroplet.phi_to_X(1, reaction_tuple)
F_over_O = gas.Y[Fu_ind]/gas.Y[Ox_ind]
flow_inlet,initial_conds = CCDroplet.get_initial_flow_vals(gas,reaction_tuple,chamber_params,inlet_conds,rho_l,F_over_O)
dotm_Ox0 = flow_inlet.dotm_Ox # kg/s
# Additional Python step: create vectors to store data
# try if it's a named_tuple; then try if it's a panda DataFrame
try:
NUM_STEPS = len(oderesults[0])
except:
NUM_STEPS = oderesults.count()[0]
dotm_l = np.zeros(NUM_STEPS)
dotm_g = np.zeros(NUM_STEPS)
phi_g = np.zeros(NUM_STEPS)
v_g = np.zeros(NUM_STEPS)
dotm_l[0] = flow_inlet.dotm_l
dotm_g[0] = flow_inlet.dotm_g
phi_g[0] = inlet_conds.phi_g
v_g[0] = flow_inlet.v_g
# first try if oderesults is a namedtuple; then try if it's a panda DataFrame
try:
D_0 = oderesults.D[0,0]
except:
D_0 = oderesults.D.loc[0]
for k in range(1,NUM_STEPS):
# first try if oderesults is a namedtuple; then try if it's a panda DataFrame
try:
dotm_lx = flow_inlet.dotm_l* (oderesults.D[k]/D_0)**3
except:
dotm_lx = flow_inlet.dotm_l*(oderesults.D.iloc[k]/D_0)**3
dotm_gx = flow_inlet.dotm_g + flow_inlet.dotm_l - dotm_lx
phi_gx = ((dotm_gx/dotm_Ox0)-1)/F_over_O
gas.X = CCDroplet.phi_to_X(phi_gx,reaction_tuple)
MW_gphi_g = gas.mean_molecular_weight
try:
v_gx = dotm_gx*ct.gas_constant*oderesults.T_g[k]/(MW_gphi_g*P*chamber_params.A_cc)
except:
v_gx = dotm_gx*ct.gas_constant*oderesults.T_g.iloc[k]/(MW_gphi_g*P*chamber_params.A_cc)
dotm_l[k] = dotm_lx
dotm_g[k] = dotm_gx
phi_g[k] = phi_gx
v_g[k] = v_gx
flows = CCDroplet.Flow_Tuple(dotm_l=dotm_l,dotm_Ox=dotm_Ox0,dotm_g=dotm_g,v_g=v_g)
return flows, phi_g