added plotting capabilities and tests (note: no colorbar yet for colorized plt)

CDTools/tools/image_processing.py

@@ -7,10 +7,10 @@ from CDTools.tools import cmath
 
 def centroid(im, dims=2):
     """Returns the centroid of an image or a stack of images
-    
+
     By default, the last two dimensions are used in the calculation
     and the remainder of the dimensions are passed through.
-    
+
     Beware that the meaning of the centroid is not well defined if your
     image contains values less than 0
 
@@ -34,14 +34,14 @@ def centroid(im, dims=2):
 
 def centroid_sq(im, dims=2, comp=False):
     """Returns the centroid of the square of an image or stack of images
-    
+
     By default, the last two dimensions are used in the calculation
     and the remainder of the dimensions are passed through.
 
     If the "comp" flag is set, it will be assumed that the last dimension
     represents the real and imaginary part of a complex number, and the
     centroid will be calculated for the magnitude squared of those numbers
-    
+
     Args:
         im (t.Tensor) : An image or stack of images to calculate from
         dims (int) : Default 2, how many trailing dimensions to calculate for
@@ -56,13 +56,13 @@ def centroid_sq(im, dims=2, comp=False):
 
     return centroid(im_sq, dims=dims)
 
-    
+
 def find_subpixel_shift(im1, im2, search_around=(0,0), resolution=10):
     """Calculates the subpixel shift between two images by maximizing the autocorrelation
-    
+
     This function only searches in a 2 pixel by 2 pixel box around the
     specified search_around parameter. The calculation is done using the
-    approach outlined in "Efficient subpixel image registration algorithms",
+    approach outlined in "Efficient subpixel image registration algorithms",
     Optics Express (2008) by Manual Guizar-Sicarios et al.
 
     Args:
@@ -77,7 +77,7 @@ def find_pixel_shift(im1, im2):
 
     This function simply takes the circular correlation with an FFT and
     returns the position of the maximum of that correlation
-    
+
     Args:
         im1 (t.Tensor): The first real or complex-valued torch tensor
         im2 (t.Tensor): The second real or complex-valued torch tensor
@@ -93,10 +93,9 @@ def find_shift(im1, im2, resolution=10):
     This function starts by calculating the maximum shift to integer
     pixel resolution, and then searchers the nearby area to calculate a
     subpixel shift
-    
+
     Args:
         im1 (t.Tensor): The first real or complex-valued torch tensor
         im2 (t.Tensor): The second real or complex-valued torch tensor
         resolution (int): Default is 10, the resolution to calculate to in units of 1/n
     """
-