def fit(self):
from summer import PPF_summer
Tc = Props(self.RefString, 'Tcrit')
rhoc = Props(self.RefString, 'rhocrit')
self.PPF = PPF_summer(Tc/self.T,self.rho/rhoc)
self.PPF.set_constants(self.T0,self.D0,self.L0,6)
self.N = scipy.optimize.minimize(self.OBJECTIVE, np.array(list(self.N0)+list(self.T0)), options = dict(maxiter = 20)).x
h = h5py.File('fit_coeffs.h5','a')
grp = h.create_group(self.Ref)
grp.create_dataset("n", data = np.array(self.N[0:len(self.N)//2]), compression = "gzip")
grp.create_dataset("t", data = np.array(self.N[len(self.N)//2::]), compression = "gzip")
h.close()
class ResidualPartFitter(object):
def __init__(self, Ref):
self.Ref = Ref
self.RefString, self.N0, self.T0, self.D0, self.L0 = get_fluid_constants(Ref)
def generate_1phase_data(self):
Tc = Props(self.RefString, 'Tcrit')
rhoc = Props(self.RefString, 'rhocrit')
TTT, RHO, PPP = [], [], []
for _T in np.linspace(220, 450, 300):
print _T
for _rho in np.logspace(np.log10(1e-10), np.log10(2.5*rhoc), 300):
try:
if _T > Tc:
p = Props('P', 'T', _T, 'D', _rho, self.RefString)
else:
DL = Props('D', 'T', _T, 'Q', 0, self.RefString)
DV = Props('D', 'T', _T, 'Q', 1, self.RefString)
if _rho < DV or _rho > DL:
p = Props('P', 'T', _T, 'D', _rho, self.RefString)
else:
p = None
if p is not None:
TTT.append(_T)
RHO.append(_rho)
PPP.append(p)
except ValueError as VE:
print VE
pass
h = h5py.File('T_rho_p.h5','w')
grp = h.create_group(self.Ref)
grp.create_dataset("T",data = np.array(TTT),compression = "gzip")
grp.create_dataset("rho", data = np.array(RHO),compression = "gzip")
grp.create_dataset("p", data = np.array(PPP),compression = "gzip")
h.close()
def load_data(self):
h = h5py.File('T_rho_p.h5','r')
self.T = h.get(self.Ref + '/T').value
self.rho = h.get(self.Ref + '/rho').value
self.p = h.get(self.Ref + '/p').value
def pressure_from_EOS(self, N):
self.PPF.n = N[0:len(N)//2]
self.PPF.t = N[len(N)//2::]
ddD1 = self.PPF.dphir_dDelta()
Tc = Props(self.RefString, 'Tcrit')
rhoc = Props(self.RefString, 'rhocrit')
R = 8.314472/Props(self.RefString,'molemass')
p = (self.rho*R*self.T)*(1+self.rho/rhoc*ddD1)
return np.array(p,ndmin=1).T
def OBJECTIVE(self, N):
pPPF = self.pressure_from_EOS(N)
RMS = np.sqrt(np.mean(np.power((pPPF-self.p)/self.p, 2)))
print RMS
return RMS
def fit(self):
from summer import PPF_summer
Tc = Props(self.RefString, 'Tcrit')
rhoc = Props(self.RefString, 'rhocrit')
self.PPF = PPF_summer(Tc/self.T,self.rho/rhoc)
self.PPF.set_constants(self.T0,self.D0,self.L0,6)
self.N = scipy.optimize.minimize(self.OBJECTIVE, np.array(list(self.N0)+list(self.T0)), options = dict(maxiter = 20)).x
h = h5py.File('fit_coeffs.h5','a')
grp = h.create_group(self.Ref)
grp.create_dataset("n", data = np.array(self.N[0:len(self.N)//2]), compression = "gzip")
grp.create_dataset("t", data = np.array(self.N[len(self.N)//2::]), compression = "gzip")
h.close()