# HG changeset patch
# User Xavier Glorot <glorotxa@iro.umontreal.ca>
# Date 1264792154 18000
# Node ID 47e7202d4f190eaf91bfcf06e6fdfe2873313b46
# Parent  442789c94b275d1fd659cc66530ff6e36d562a89
Array format handling bug fix for thick.py

diff -r 442789c94b27 -r 47e7202d4f19 transformations/thick.py
--- a/transformations/thick.py	Fri Jan 29 11:44:12 2010 -0500
+++ b/transformations/thick.py	Fri Jan 29 14:09:14 2010 -0500
@@ -69,15 +69,14 @@
             maxi = float(N.max(image))
             mini = float(N.min(image))
             
-            if maxi>1.0:
-                image=image/maxi
+            imagenorm=image/maxi
             
             if self.meth==1:
                 trans=scipy.ndimage.morphology.grey_dilation\
-                    (image,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
+                    (imagenorm,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
             else:
                 trans=scipy.ndimage.morphology.grey_erosion\
-                    (image,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
+                    (imagenorm,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
             
             #------renormalizing
             maxit = N.max(trans)
@@ -92,9 +91,10 @@
         if image.shape == (self.__nx__,self.__ny__):
             return self.transform_1_image(image)
         if image.ndim == 3:
+            newimage = copy.copy(image)
             for i in range(image.shape[0]):
-                image[i,:,:] = self.transform_1_image(image[i,:,:])
-            return N.reshape(newimage,image.shape)
+                newimage[i,:,:] = self.transform_1_image(image[i,:,:])
+            return newimage
         if image.ndim == 2 and image.shape != (self.__nx__,self.__ny__):
             newimage = N.reshape(image,(image.shape[0],self.__nx__,self.__ny__))
             for i in range(image.shape[0]):