black without mortimer

scripts/mngseg.py

@@ -6,7 +6,7 @@ import aplpy
 
 
 def make_images(im, wt, M, meanim, label):
-    """ show the Gaussian and coherent part of the image """
+    """show the Gaussian and coherent part of the image"""
 
     total = np.sum(wt[:M, :, :], axis=0).real + meanim
     coherent = np.sum(wt[M : 2 * M, :, :], axis=0).real + meanim
@@ -52,7 +52,7 @@ def make_images(im, wt, M, meanim, label):
 
 
 def scale_images(thingy, M, label, scale=14, mode="wt"):
-    """ visualize wt or S11a for a specific scale. Remark S11a = wt^2"""
+    """visualize wt or S11a for a specific scale. Remark S11a = wt^2"""
     total = thingy[scale, :, :].real
     coherent = thingy[M + scale, :, :].real
     Gaussian = thingy[2 * M + scale, :, :].real
@@ -93,7 +93,7 @@ def scale_images(thingy, M, label, scale=14, mode="wt"):
 
 
 def plot_each_scale(S11a, wav_k, q, label, coherent=False, reso=1):
-    """ plot histogram at a certain scale """
+    """plot histogram at a certain scale"""
     nsize = len(S11a[0, 0, :])
     M = len(q)
     for scl in range(0, M):
@@ -237,7 +237,7 @@ def load_results(label):
 
 
 def analyse_sim(im, load=False, scale_image=False):
-    """ Do the MnGseg analysis """
+    """Do the MnGseg analysis"""
     meanim = np.mean(im)
     imzm = im - meanim
     M = nb_scale(im.shape)
@@ -264,7 +264,6 @@ def analyse_sim(im, load=False, scale_image=False):
     # make images of the Gaussian and coherent part
     make_images(im, wt, M, meanim, label)
 
-    
     if scale_image:
         # (optional) make the image for each scale
         for s in range(fit_min, fit_max + 1):