def fit_phi():
mod = Model(OBJECTIVE_phi)
mydata = Data(XXX.copy(), PHI)
beta0 = [100 for _ in range(N)]
myodr = ODR(mydata, mod, beta0=beta0)
myoutput = myodr.run()
myoutput.pprint()
print myoutput.sum_square
YFIT = OBJECTIVE_theta(myoutput.beta,XXX)
plt.plot(PHI,YFIT,'o',mfc='none')
plt.show()
ERR = YFIT-PHI
from CoolProp.Plots.Plots import Trho
Trho(fluid)
plt.plot(np.array(RHO.vec)[np.abs(ERR)<5e-2],np.array(TTT.vec)[np.abs(ERR)<5e-2],'.')
MAE = np.mean(np.abs(YFIT/PHI-1))*100
plt.show()
return myoutput.beta,MAE
except ValueError:
print('TTSE failed: %s %s' % (T, rho))
values.append((T, rho, 0, 0))
pass
return values
fluid = 'R245fa'
values = check_Trho(param='P', fluid=fluid)
if len(values) == 0:
print('good')
T, rho, values_withTTSE, values_noTTSE = zip(*values)
CP.disable_TTSE_LUT(fluid)
Trho(fluid)
plt.plot(rho, T, '.', mfc='none')
plt.savefig('Trho_TTSE_Validation.png', dpi=300)
plt.gca().set_xscale('log')
plt.show()
quit()
def check_Pother(N=5000, param='T', other='S', fluid='R245fa'):
values = []
CP.enable_TTSE_LUT(fluid)
try:
CP.Props('D', 'P', CP.Props(fluid, 'ptriple') + 1, 'Q', 1, fluid)
except: