diff --git a/ptsa/data/events.py b/ptsa/data/events.py
index 2a125d7..273e1cf 100644
--- a/ptsa/data/events.py
+++ b/ptsa/data/events.py
@@ -97,12 +97,15 @@ def add_fields(self,**fields):
             if self.dtype.fields.has_key(name):
                 # already exists
                 raise ValueError('Field "'+name+'" already exists.')
-            
+
             # append the array and name
             if(isinstance(data,np.dtype)|
-               isinstance(data,type)|isinstance(data,str)):
+               isinstance(data,type)):
                 # add empty array the length of the data
                 arrays.append(np.empty(len(self),data))
+            elif isinstance(data,str):
+                # populate the string-like data in an array
+                arrays.append(np.full(len(self),data,dtype='|S{:d}'.format(len(data))))
             else:
                 # add the data as an array
                 arrays.append(data)
diff --git a/ptsa/wavelet.py b/ptsa/wavelet.py
index 50592e8..c08d2c8 100644
--- a/ptsa/wavelet.py
+++ b/ptsa/wavelet.py
@@ -67,12 +67,12 @@ def swt(data, wavelet, level=None):
             odd_indices = indices[1::2] 
             
             # get the even
-            (cA1,cD1) = pywt.dwt(idata[indices], wavelet, 'per')
+            (cA1,cD1) = pywt.dwt(idata[indices], wavelet, 'periodization')
             cA[even_indices] = cA1
             cD[even_indices] = cD1
 
             # then the odd
-            (cA1,cD1) = pywt.dwt(np.roll(idata[indices],-1), wavelet, 'per')
+            (cA1,cD1) = pywt.dwt(np.roll(idata[indices],-1), wavelet, 'periodization')
             cA[odd_indices] = cA1
             cD[odd_indices] = cD1
 
@@ -120,8 +120,8 @@ def iswt(coefficients, wavelet):
 
             # perform the inverse dwt on the selected indices,
             # making sure to use periodic boundary conditions
-            x1 = pywt.idwt(output[even_indices], cD[even_indices], wavelet, 'per') 
-            x2 = pywt.idwt(output[odd_indices], cD[odd_indices], wavelet, 'per') 
+            x1 = pywt.idwt(output[even_indices], cD[even_indices], wavelet, 'periodization') 
+            x2 = pywt.idwt(output[odd_indices], cD[odd_indices], wavelet, 'periodization') 
 
             # perform a circular shift right
             x2 = np.roll(x2, 1)
diff --git a/ptsa/wica.py b/ptsa/wica.py
index 76ef3cc..f7424b8 100644
--- a/ptsa/wica.py
+++ b/ptsa/wica.py
@@ -247,7 +247,7 @@ def _clean_comp(comp, Kthr, L, thld=None):
     return comp, thld
 
     
-def remove_strong_artifacts(data, A, icaEEG, Comp, Kthr=1.25, F=256,
+def remove_strong_artifacts(icaEEG, Comp, Kthr=1.25, F=256,
                             Cthr=None, num_mp_procs=0):
     """
     % This function denoise high amplitude artifacts (e.g. ocular) and remove them from the
@@ -487,14 +487,13 @@ def clean(self, comp_inds=None, Kthr=2.5, num_mp_procs=0):
         # remove strong artifacts
         if (not self._pure_range[0] is None) or (not self._pure_range[1] is None):
             # figure out the thresh for the range
-            Cthr = remove_strong_artifacts(self._data[:,self._pure_range[0]:self._pure_range[1]], self.ICA_weights,
-                                           self._components[:,self._pure_range[0]:self._pure_range[1]],
+            Cthr = remove_strong_artifacts(self._components[:,self._pure_range[0]:self._pure_range[1]],
                                            comp_inds, Kthr,
                                            self._samplerate,
                                            num_mp_procs=num_mp_procs)
         else:
             Cthr = None
-        Cthr = remove_strong_artifacts(self._data,self.ICA_weights,self._components, 
+        Cthr = remove_strong_artifacts(self._components,
                                        comp_inds, Kthr,
                                        self._samplerate, Cthr,
                                        num_mp_procs=num_mp_procs)