diff --git a/src/calculate/optimize/CheKiPEUQ_from_Frhodo.py b/src/calculate/optimize/CheKiPEUQ_from_Frhodo.py
index e968f85..d311152 100644
--- a/src/calculate/optimize/CheKiPEUQ_from_Frhodo.py
+++ b/src/calculate/optimize/CheKiPEUQ_from_Frhodo.py
@@ -102,7 +102,7 @@ def extract_larger_delta_and_make_sigma_values(initial_guess, lower_bound, upper
         upper_delta = np.abs(upper_bound[index]-initial_guess[index])
         lower_delta = np.abs(lower_bound[index]-initial_guess[index])
         max_delta = np.max([upper_delta,lower_delta])
-        current_sigma = max_delta/float(sigma_multiple)
+        current_sigma = max_delta/np.float(sigma_multiple)
         sigma_values[index] = current_sigma
     return sigma_values
     
diff --git a/src/calculate/optimize/CheKiPEUQ_local/InverseProblem.py b/src/calculate/optimize/CheKiPEUQ_local/InverseProblem.py
index e4a8158..38799cc 100644
--- a/src/calculate/optimize/CheKiPEUQ_local/InverseProblem.py
+++ b/src/calculate/optimize/CheKiPEUQ_local/InverseProblem.py
@@ -176,8 +176,8 @@ def __init__(self, UserInput = None):
             if len(self.UserInput.responses['responses_observed_weighting']) > 0:
                 UserInput.responses_observed_weighting = np.array(nestedObjectsFunctions.makeAtLeast_2dNested(UserInput.responses['responses_observed_weighting']))
                 UserInput.responses_observed_weighting = nestedObjectsFunctions.convertInternalToNumpyArray_2dNested(UserInput.responses_observed_weighting)
-                UserInput.responses_observed_weighting = UserInput.responses_observed_weighting.astype(float)
-                UserInput.responses_observed_weight_coefficients = copy.deepcopy(UserInput.responses_observed_weighting).astype(float) #initialize the weight_coefficients
+                UserInput.responses_observed_weighting = UserInput.responses_observed_weighting.astype(np.float)
+                UserInput.responses_observed_weight_coefficients = copy.deepcopy(UserInput.responses_observed_weighting).astype(np.float) #initialize the weight_coefficients
                 #We'll apply it 1 response at a time.
                 for responseIndex, responseWeightingArray in enumerate(UserInput.responses_observed_weighting):
                     if 0 in responseWeightingArray: #we can't have zeros in weights. So if we have any zeros, we will set the weighting of those to 1E6 times less than other values.
diff --git a/src/calculate/optimize/misc_fcns.py b/src/calculate/optimize/misc_fcns.py
index 11c2097..ed3c640 100644
--- a/src/calculate/optimize/misc_fcns.py
+++ b/src/calculate/optimize/misc_fcns.py
@@ -79,7 +79,6 @@ def set_bnds(mech, rxnIdx, keys, coefNames):
 
     return coef_bnds
 
-
 def set_arrhenius_bnds(x0, coefNames):
     bnds = [[], []]
     for n, coefName in enumerate(coefNames):
diff --git a/src/error_window.py b/src/error_window.py
index f86f943..6fcf2d3 100644
--- a/src/error_window.py
+++ b/src/error_window.py
@@ -80,10 +80,7 @@ def excepthook(type, value, tback):
 
         # call the default handler
         sys.__excepthook__(type, value, tback)
-
-        if "Deprecat" in text or "deprecat" in text: # ignore deprecation warnings
-            pass
-        else:
-            Error_Window(app, path, text)    
+        
+        Error_Window(app, path, text)    
         
     return excepthook
\ No newline at end of file
diff --git a/src/mech_widget.py b/src/mech_widget.py
index f3c3b7f..6c7ef01 100644
--- a/src/mech_widget.py
+++ b/src/mech_widget.py
@@ -97,6 +97,14 @@ def set_trees(self, mech):
         self._set_mech_tree(self.mech_tree_data)
 
     def _set_mech_tree_data(self, selection, mech):
+        def get_coef_abbreviation(coefName):
+            if 'activation_energy' == coefName:
+                return 'Ea'
+            elif 'pre_exponential_factor' == coefName:
+                return 'A'
+            elif 'temperature_exponent' == coefName:
+                return 'n'
+
         parent = self.parent()
         data = []
         for rxnIdx, rxn in enumerate(mech.gas.reactions()):
@@ -130,7 +138,6 @@ def _set_mech_tree_data(self, selection, mech):
                 data.append({'num': rxnIdx, 'eqn': rxn.equation, 'type': rxn_type, 
                              'coeffs': coeffs, 'coeffs_order': coeffs_order})
             else:
-
                 data.append({'num': rxnIdx, 'eqn': rxn.equation, 'type': rxn_type})
                 # raise Exception("Equation type is not currently implemented for:\n{:s}".format(rxn.equation))