diff --git a/rmgpy/pdep/network.py b/rmgpy/pdep/network.py index 85f9142fe84..8b69886245d 100644 --- a/rmgpy/pdep/network.py +++ b/rmgpy/pdep/network.py @@ -75,8 +75,8 @@ class Network(object): `active_j_rotor` ``True`` if the J-rotor is treated as active, ``False`` if treated as adiabatic `rmgmode` ``True`` if in RMG mode, ``False`` otherwise ----------------------- ---------------------------------------------------- - `eqRatios` An array containing concentration of each isomer and reactant channel present at equilibrium - `coll_freq` An array of the frequency of collision between + `eq_ratios` An array containing concentration of each isomer and reactant channel present at equilibrium + `coll_freq` An array of the frequency of collision between `Mcoll` Matrix of first-order rate coefficients for collisional population transfer between grains for each isomer `dens_states` 3D np array of stable configurations, number of grains, and number of J ======================= ==================================================== @@ -269,7 +269,7 @@ def calculate_rate_coefficients(self, Tlist, Plist, method, error_check=True): K[t, p, :, :] = self.K # Check that the k(T,P) values satisfy macroscopic equilibrium - eq_ratios = self.eqRatios + eq_ratios = self.eq_ratios for i in range(n_isom + n_reac): for j in range(i): Keq0 = K[t, p, j, i] / K[t, p, i, j] @@ -693,7 +693,7 @@ def calculate_microcanonical_rates(self): rxn.network_kinetics.get_rate_coefficient(temperature) # Determine the expected value of the equilibrium constant (Kc) - Keq_expected = self.eqRatios[prod] / self.eqRatios[reac] + Keq_expected = self.eq_ratios[prod] / self.eq_ratios[reac] # Determine the actual values of k(T) and Keq C0 = 1e5 / (constants.R * temperature) @@ -831,7 +831,7 @@ def calculate_equilibrium_ratios(self): if self.products[i].has_statmech() or self.products[i].has_thermo(): G = self.products[i].get_free_energy(temperature) eq_ratios[n_isom + n_reac + i] = math.exp(-G / constants.R / temperature) * conc ** (len(self.products[i].species) - 1) - self.eqRatios = eq_ratios + self.eq_ratios = eq_ratios return eq_ratios / np.sum(eq_ratios) def calculate_collision_model(self):