diff --git a/vip_hci/metrics/detection.py b/vip_hci/metrics/detection.py
index dc2813b7..4796578d 100644
--- a/vip_hci/metrics/detection.py
+++ b/vip_hci/metrics/detection.py
@@ -322,6 +322,7 @@ def print_abort():
     yy_out = []
     xx_out = []
     snr_list = []
+    snr_final = []
 
     if mode in ('lpeaks', 'log', 'dog'):
         xx -= pad
@@ -342,6 +343,7 @@ def print_abort():
                 _ = frame_report(array, fwhm, (x, y), verbose=verbose)
             yy_final.append(y)
             xx_final.append(x)
+            snr_final.append(snr_value)
         else:
             yy_out.append(y)
             xx_out.append(x)
@@ -353,17 +355,18 @@ def print_abort():
     if verbose:
         print(sep)
 
-    if debug or full_output:
+    if debug:
         table_full = pn.DataFrame({'y': yy.tolist(),
                                    'x': xx.tolist(),
                                    'px_snr': snr_list})
         table_full.sort_values('px_snr')
+        print(table_full)
 
     yy_final = np.array(yy_final)
     xx_final = np.array(xx_final)
     yy_out = np.array(yy_out)
     xx_out = np.array(xx_out)
-    table = pn.DataFrame({'y': yy_final.tolist(), 'x': xx_final.tolist()})
+    table = pn.DataFrame({'y': yy_final.tolist(), 'x': xx_final.tolist(), 'px_snr': snr_final})
 
     if plot:
         coords = tuple(zip(xx_out.tolist() + xx_final.tolist(),
@@ -373,9 +376,6 @@ def print_abort():
         plot_frames(array, dpi=120, circle=coords, circle_alpha=circlealpha,
                     circle_label=True, circle_radius=fwhm, **kwargs)
 
-    if debug:
-        print(table_full)
-
     if full_output:
         return table
     else:
diff --git a/vip_hci/preproc/badframes.py b/vip_hci/preproc/badframes.py
index c54285ac..8df78c09 100644
--- a/vip_hci/preproc/badframes.py
+++ b/vip_hci/preproc/badframes.py
@@ -63,9 +63,14 @@ def cube_detect_badfr_pxstats(array, mode='annulus', in_radius=10, width=10,
     """
     check_array(array, 3, msg='array')
 
-    if in_radius+width > array[0].shape[0]/2:
-        msgve = 'Inner radius and annulus size are too big (out of boundaries)'
-        raise ValueError(msgve)
+    if mode == 'annulus':
+        if in_radius + width > array[0].shape[0] / 2:
+            msgve = 'Inner radius and annulus size are too big (out of boundaries)'
+            raise ValueError(msgve)
+    elif mode == 'circle':
+        if in_radius > array[0].shape[0] / 2:
+            msgve = 'Radius size is too big (out of boundaries)'
+            raise ValueError(msgve)
 
     if verbose:
         start_time = time_ini()
diff --git a/vip_hci/preproc/recentering.py b/vip_hci/preproc/recentering.py
index 25da3466..559f6f20 100644
--- a/vip_hci/preproc/recentering.py
+++ b/vip_hci/preproc/recentering.py
@@ -1476,7 +1476,8 @@ def cube_recenter_2dfit(array, xy=None, fwhm=4, subi_size=5, model='gauss',
 
     if nproc == 1:
         res = []
-        print('2d {}-fitting'.format(model))
+        if verbose:
+            print('2d {}-fitting'.format(model))
         for i in Progressbar(range(n_frames), desc="frames", verbose=verbose):
             if model == "2gauss":
                 args = [array, i, subi_size, pos_y, pos_x, debug, fwhm[i],
diff --git a/vip_hci/stats/clip_sigma.py b/vip_hci/stats/clip_sigma.py
index b9744f9f..59f2dd9a 100644
--- a/vip_hci/stats/clip_sigma.py
+++ b/vip_hci/stats/clip_sigma.py
@@ -287,7 +287,7 @@ def _clip_array(array, lower_sigma, upper_sigma, bpm_mask_ori,
         if bpm_mask_ori is None:
             gpm_ori = np.ones(array.shape)
         else:
-            gpm_ori = np.ones(array.shape)-bpm_mask_ori
+            gpm_ori = np.ones(array.shape) - bpm_mask_ori
         
         ny, nx = array.shape
         bpm = np.ones(array.shape)
@@ -331,7 +331,11 @@ def _clip_array(array, lower_sigma, upper_sigma, bpm_mask_ori,
                                     x-hbox_l:x+hbox_r+1]
                     gp_arr = gpm_ori[y-hbox_b:y+hbox_t+1,
                                      x-hbox_l:x+hbox_r+1]
-                    neighbours = sub_arr[np.where(gp_arr)].flatten()
+                    gp_idx = np.nonzero(gp_arr)
+                    neighbours = []
+                    for n, (i, j) in enumerate(zip(gp_idx[0], gp_idx[1])):
+                        neighbours.append(sub_arr[i, j])
+                    neighbours = np.array(neighbours)
                     neigh_list = []
                     remove_itself = True
                     for i in range(neighbours.shape[0]):