Update fit_coeffs.py

Minor bug catch

src/calculate/optimize/fit_coeffs.py

@@ -21,6 +21,8 @@
 max_pos_system_value = (np.finfo(float).max*(1E-20))**(1/2)
 min_ln_val = np.log(min_pos_system_value)
 max_ln_val = np.log(max_pos_system_value)
+min_log_val = np.log10(min_pos_system_value)
+max_log_val = np.log10(max_pos_system_value)
 
 default_arrhenius_coefNames = ['activation_energy', 'pre_exponential_factor', 'temperature_exponent']
 default_Troe_coefNames = ['activation_energy_0', 'pre_exponential_factor_0', 'temperature_exponent_0', 
@@ -755,6 +757,11 @@ def ln_Troe(self, T, *x):   # LPL, HPL, Fcent
             try:
                 P_r = k_0/k_inf*M
                 log_P_r = np.log10(P_r)
+
+                #log_P_r = np.log10(k_0) - np.log10(k_inf) + np.log10(M)
+                #log_P_r[log_P_r < min_log_val] = min_log_val
+                #log_P_r[log_P_r > max_log_val] = max_log_val
+                #P_r = np.power(10, log_P_r)
             except:
                 return np.ones_like(M)*max_pos_system_value           
 
@@ -764,7 +771,11 @@ def ln_Troe(self, T, *x):   # LPL, HPL, Fcent
         f1 = (log_P_r + C)/(N - 0.14*(log_P_r + C))
 
         ln_F = np.log(Fcent)/(1 + f1**2)
-        ln_k_calc = np.log(k_inf*P_r/(1 + P_r)) + ln_F
+        with np.errstate(all='raise'):
+            try:
+                ln_k_calc = np.log(k_inf*P_r/(1 + P_r)) + ln_F
+            except:
+                return np.ones_like(M)*max_pos_system_value   
 
         return ln_k_calc