def load_all_methods(self):
r'''Method which picks out coefficients for the specified chemical
from the various dictionaries and DataFrames storing it. All data is
stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`,
and :obj:`all_methods` as a set of methods for which the data exists for.
Called on initialization only. See the source code for the variables at
which the coefficients are stored. The coefficients can safely be
altered once the class is initialized. This method can be called again
to reset the parameters.
'''
methods = []
Tmins, Tmaxs = [], []
if self.CASRN in Mulero_Cachadina_data.index:
methods.append(STREFPROP)
_, sigma0, n0, sigma1, n1, sigma2, n2, Tc, self.STREFPROP_Tmin, self.STREFPROP_Tmax = _Mulero_Cachadina_data_values[Mulero_Cachadina_data.index.get_loc(self.CASRN)].tolist()
self.STREFPROP_coeffs = [sigma0, n0, sigma1, n1, sigma2, n2, Tc]
Tmins.append(self.STREFPROP_Tmin); Tmaxs.append(self.STREFPROP_Tmax)
if self.CASRN in Somayajulu_data_2.index:
methods.append(SOMAYAJULU2)
_, self.SOMAYAJULU2_Tt, self.SOMAYAJULU2_Tc, A, B, C = _Somayajulu_data_2_values[Somayajulu_data_2.index.get_loc(self.CASRN)].tolist()
self.SOMAYAJULU2_coeffs = [A, B, C]
Tmins.append(self.SOMAYAJULU2_Tt); Tmaxs.append(self.SOMAYAJULU2_Tc)
if self.CASRN in Somayajulu_data.index:
methods.append(SOMAYAJULU)
_, self.SOMAYAJULU_Tt, self.SOMAYAJULU_Tc, A, B, C = _Somayajulu_data_values[Somayajulu_data.index.get_loc(self.CASRN)].tolist()
self.SOMAYAJULU_coeffs = [A, B, C]
Tmins.append(self.SOMAYAJULU_Tt); Tmaxs.append(self.SOMAYAJULU_Tc)
if self.CASRN in _VDISaturationDict:
methods.append(VDI_TABULAR)
Ts, props = VDI_tabular_data(self.CASRN, 'sigma')
self.VDI_Tmin = Ts[0]
self.VDI_Tmax = Ts[-1]
self.tabular_data[VDI_TABULAR] = (Ts, props)
Tmins.append(self.VDI_Tmin); Tmaxs.append(self.VDI_Tmax)
if self.CASRN in Jasper_Lange_data.index:
methods.append(JASPER)
_, a, b, self.JASPER_Tmin, self.JASPER_Tmax= _Jasper_Lange_data_values[Jasper_Lange_data.index.get_loc(self.CASRN)].tolist()
self.JASPER_coeffs = [a, b]
Tmins.append(self.JASPER_Tmin); Tmaxs.append(self.JASPER_Tmax)
if all((self.Tc, self.Vc, self.omega)):
methods.append(MIQUEU)
Tmins.append(0.0); Tmaxs.append(self.Tc)
if all((self.Tb, self.Tc, self.Pc)):
methods.append(BROCK_BIRD)
methods.append(SASTRI_RAO)
Tmins.append(0.0); Tmaxs.append(self.Tc)
if all((self.Tc, self.Pc, self.omega)):
methods.append(PITZER)
methods.append(ZUO_STENBY)
Tmins.append(0.0); Tmaxs.append(self.Tc)
self.all_methods = set(methods)
if Tmins and Tmaxs:
# Note: All methods work right down to 0 K.
self.Tmin = min(Tmins)
self.Tmax = max(Tmaxs)
def load_all_methods(self):
r'''Method which picks out coefficients for the specified chemical
from the various dictionaries and DataFrames storing it. All data is
stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`,
and :obj:`all_methods` as a set of methods for which the data exists for.
Called on initialization only. See the source code for the variables at
which the coefficients are stored. The coefficients can safely be
altered once the class is initialized. This method can be called again
to reset the parameters.
'''
methods = []
Tmins, Tmaxs = [], []
if has_CoolProp and self.CASRN in coolprop_dict:
methods.append(COOLPROP)
self.CP_f = coolprop_fluids[self.CASRN]
Tmins.append(self.CP_f.Tt); Tmaxs.append(self.CP_f.Tc)
if self.CASRN in _VDISaturationDict:
methods.append(VDI_TABULAR)
Ts, props = VDI_tabular_data(self.CASRN, 'Hvap')
self.VDI_Tmin = Ts[0]
self.VDI_Tmax = Ts[-1]
self.tabular_data[VDI_TABULAR] = (Ts, props)
Tmins.append(self.VDI_Tmin); Tmaxs.append(self.VDI_Tmax)
if self.CASRN in CRCHvap_data.index and not np.isnan(CRCHvap_data.at[self.CASRN, 'HvapTb']):
methods.append(CRC_HVAP_TB)
self.CRC_HVAP_TB_Tb = float(CRCHvap_data.at[self.CASRN, 'Tb'])
self.CRC_HVAP_TB_Hvap = float(CRCHvap_data.at[self.CASRN, 'HvapTb'])
if self.CASRN in CRCHvap_data.index and not np.isnan(CRCHvap_data.at[self.CASRN, 'Hvap298']):
methods.append(CRC_HVAP_298)
self.CRC_HVAP_298 = float(float(CRCHvap_data.at[self.CASRN, 'Hvap298']))
if self.CASRN in GharagheiziHvap_data.index:
methods.append(GHARAGHEIZI_HVAP_298)
self.GHARAGHEIZI_HVAP_298_Hvap = float(GharagheiziHvap_data.at[self.CASRN, 'Hvap298'])
if all((self.Tc, self.omega)):
methods.extend(self.CSP_methods)
Tmaxs.append(self.Tc); Tmins.append(0)
if all((self.Tc, self.Pc)):
methods.append(CLAPEYRON)
Tmaxs.append(self.Tc); Tmins.append(0)
if all((self.Tb, self.Tc, self.Pc)):
methods.extend(self.boiling_methods)
Tmaxs.append(self.Tc); Tmins.append(0)
self.all_methods = set(methods)
if Tmins and Tmaxs:
self.Tmin, self.Tmax = min(Tmins), max(Tmaxs)
def load_all_methods(self):
r'''Method which picks out coefficients for the specified chemical
from the various dictionaries and DataFrames storing it. All data is
stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`,
and :obj:`all_methods` as a set of methods for which the data exists for.
Called on initialization only. See the source code for the variables at
which the coefficients are stored. The coefficients can safely be
altered once the class is initialized. This method can be called again
to reset the parameters.
'''
methods = []
Tmins, Tmaxs = [], []
if self.CASRN in WagnerMcGarry.index:
methods.append(WAGNER_MCGARRY)
_, A, B, C, D, self.WAGNER_MCGARRY_Pc, self.WAGNER_MCGARRY_Tc, self.WAGNER_MCGARRY_Tmin = _WagnerMcGarry_values[
WagnerMcGarry.index.get_loc(self.CASRN)].tolist()
self.WAGNER_MCGARRY_coefs = [A, B, C, D]
Tmins.append(self.WAGNER_MCGARRY_Tmin)
Tmaxs.append(self.WAGNER_MCGARRY_Tc)
if self.CASRN in WagnerPoling.index:
methods.append(WAGNER_POLING)
_, A, B, C, D, self.WAGNER_POLING_Tc, self.WAGNER_POLING_Pc, Tmin, self.WAGNER_POLING_Tmax = _WagnerPoling_values[
WagnerPoling.index.get_loc(self.CASRN)].tolist()
# Some Tmin values are missing; Arbitrary choice of 0.1 lower limit
self.WAGNER_POLING_Tmin = Tmin if not np.isnan(
Tmin) else self.WAGNER_POLING_Tmax * 0.1
self.WAGNER_POLING_coefs = [A, B, C, D]
Tmins.append(Tmin)
Tmaxs.append(self.WAGNER_POLING_Tmax)
if self.CASRN in AntoineExtended.index:
methods.append(ANTOINE_EXTENDED_POLING)
_, A, B, C, Tc, to, n, E, F, self.ANTOINE_EXTENDED_POLING_Tmin, self.ANTOINE_EXTENDED_POLING_Tmax = _AntoineExtended_values[
AntoineExtended.index.get_loc(self.CASRN)].tolist()
self.ANTOINE_EXTENDED_POLING_coefs = [Tc, to, A, B, C, n, E, F]
Tmins.append(self.ANTOINE_EXTENDED_POLING_Tmin)
Tmaxs.append(self.ANTOINE_EXTENDED_POLING_Tmax)
if self.CASRN in AntoinePoling.index:
methods.append(ANTOINE_POLING)
_, A, B, C, self.ANTOINE_POLING_Tmin, self.ANTOINE_POLING_Tmax = _AntoinePoling_values[
AntoinePoling.index.get_loc(self.CASRN)].tolist()
self.ANTOINE_POLING_coefs = [A, B, C]
Tmins.append(self.ANTOINE_POLING_Tmin)
Tmaxs.append(self.ANTOINE_POLING_Tmax)
if has_CoolProp and self.CASRN in coolprop_dict:
methods.append(COOLPROP)
self.CP_f = coolprop_fluids[self.CASRN]
Tmins.append(self.CP_f.Tmin)
Tmaxs.append(self.CP_f.Tc)
if self.CASRN in _VDISaturationDict:
methods.append(VDI_TABULAR)
Ts, props = VDI_tabular_data(self.CASRN, 'P')
self.VDI_Tmin = Ts[0]
self.VDI_Tmax = Ts[-1]
self.tabular_data[VDI_TABULAR] = (Ts, props)
Tmins.append(self.VDI_Tmin)
Tmaxs.append(self.VDI_Tmax)
if all((self.Tb, self.Tc, self.Pc)):
methods.append(BOILING_CRITICAL)
Tmins.append(0.01)
Tmaxs.append(self.Tc)
if all((self.Tc, self.Pc, self.omega)):
methods.append(LEE_KESLER_PSAT)
methods.append(AMBROSE_WALTON)
methods.append(SANJARI)
if self.eos:
methods.append(EOS)
Tmins.append(0.01)
Tmaxs.append(self.Tc)
self.all_methods = set(methods)
if Tmins and Tmaxs:
self.Tmin = min(Tmins)
self.Tmax = max(Tmaxs)
def load_all_methods(self):
r'''Method which picks out coefficients for the specified chemical
from the various dictionaries and DataFrames storing it. All data is
stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`,
and :obj:`all_methods` as a set of methods for which the data exists for.
Called on initialization only. See the source code for the variables at
which the coefficients are stored. The coefficients can safely be
altered once the class is initialized. This method can be called again
to reset the parameters.
'''
methods = []
Tmins, Tmaxs = [], []
if self.CASRN in Mulero_Cachadina_data.index:
methods.append(STREFPROP)
_, sigma0, n0, sigma1, n1, sigma2, n2, Tc, self.STREFPROP_Tmin, self.STREFPROP_Tmax = _Mulero_Cachadina_data_values[
Mulero_Cachadina_data.index.get_loc(self.CASRN)].tolist()
self.STREFPROP_coeffs = [sigma0, n0, sigma1, n1, sigma2, n2, Tc]
Tmins.append(self.STREFPROP_Tmin)
Tmaxs.append(self.STREFPROP_Tmax)
if self.CASRN in Somayajulu_data_2.index:
methods.append(SOMAYAJULU2)
_, self.SOMAYAJULU2_Tt, self.SOMAYAJULU2_Tc, A, B, C = _Somayajulu_data_2_values[
Somayajulu_data_2.index.get_loc(self.CASRN)].tolist()
self.SOMAYAJULU2_coeffs = [A, B, C]
Tmins.append(self.SOMAYAJULU2_Tt)
Tmaxs.append(self.SOMAYAJULU2_Tc)
if self.CASRN in Somayajulu_data.index:
methods.append(SOMAYAJULU)
_, self.SOMAYAJULU_Tt, self.SOMAYAJULU_Tc, A, B, C = _Somayajulu_data_values[
Somayajulu_data.index.get_loc(self.CASRN)].tolist()
self.SOMAYAJULU_coeffs = [A, B, C]
Tmins.append(self.SOMAYAJULU_Tt)
Tmaxs.append(self.SOMAYAJULU_Tc)
if self.CASRN in _VDISaturationDict:
methods.append(VDI_TABULAR)
Ts, props = VDI_tabular_data(self.CASRN, 'sigma')
self.VDI_Tmin = Ts[0]
self.VDI_Tmax = Ts[-1]
self.tabular_data[VDI_TABULAR] = (Ts, props)
Tmins.append(self.VDI_Tmin)
Tmaxs.append(self.VDI_Tmax)
if self.CASRN in Jasper_Lange_data.index:
methods.append(JASPER)
_, a, b, self.JASPER_Tmin, self.JASPER_Tmax = _Jasper_Lange_data_values[
Jasper_Lange_data.index.get_loc(self.CASRN)].tolist()
self.JASPER_coeffs = [a, b]
Tmins.append(self.JASPER_Tmin)
Tmaxs.append(self.JASPER_Tmax)
if all((self.Tc, self.Vc, self.omega)):
methods.append(MIQUEU)
Tmins.append(0.0)
Tmaxs.append(self.Tc)
if all((self.Tb, self.Tc, self.Pc)):
methods.append(BROCK_BIRD)
methods.append(SASTRI_RAO)
Tmins.append(0.0)
Tmaxs.append(self.Tc)
if all((self.Tc, self.Pc, self.omega)):
methods.append(PITZER)
methods.append(ZUO_STENBY)
Tmins.append(0.0)
Tmaxs.append(self.Tc)
if self.CASRN in VDI_PPDS_11.index:
_, Tm, Tc, A, B, C, D, E = _VDI_PPDS_11_values[
VDI_PPDS_11.index.get_loc(self.CASRN)].tolist()
self.VDI_PPDS_coeffs = [A, B, C, D, E]
self.VDI_PPDS_Tc = Tc
self.VDI_PPDS_Tm = Tm
methods.append(VDI_PPDS)
Tmins.append(self.VDI_PPDS_Tm)
Tmaxs.append(self.VDI_PPDS_Tc)
if all((self.Tb, self.Hvap_Tb, self.MW)):
# Cache Cpl at Tb for ease of calculation of Tmax
self.Cpl_Tb = self.Cpl(self.Tb) if hasattr(
self.Cpl, '__call__') else self.Cpl
if self.Cpl_Tb:
methods.append(ALEEM)
# Tmin and Tmax for this method is known
Tmax_possible = self.Tb + self.Hvap_Tb / self.Cpl_Tb
# This method will ruin solve_prop as it is typically valid
# well above Tc. If Tc is available, limit it to that.
if self.Tc:
Tmax_possible = min(self.Tc, Tmax_possible)
Tmins.append(0.0)
Tmaxs.append(Tmax_possible)
self.all_methods = set(methods)
if Tmins and Tmaxs:
# Note: All methods work right down to 0 K.
self.Tmin = min(Tmins)
self.Tmax = max(Tmaxs)