From ba328e753137498aa639e9d34f6f1e01012c9b32 Mon Sep 17 00:00:00 2001
From: Evgeni Burovski <evgeny.burovskiy@gmail.com>
Date: Sun, 7 Feb 2016 20:21:10 +0000
Subject: [PATCH] MAINT: address review comments

Use recommended idioms in the .py wrapper
---
 skimage/morphology/_skeletonize_3d.py         | 28 ++++++++-----------
 .../morphology/tests/test_skeletonize_3d.py   | 10 ++++++-
 2 files changed, 21 insertions(+), 17 deletions(-)

diff --git a/skimage/morphology/_skeletonize_3d.py b/skimage/morphology/_skeletonize_3d.py
index d041f643..768ec08b 100644
--- a/skimage/morphology/_skeletonize_3d.py
+++ b/skimage/morphology/_skeletonize_3d.py
@@ -1,7 +1,7 @@
 from __future__ import division, print_function, absolute_import
 
 import numpy as np
-from ..util import img_as_ubyte
+from ..util import img_as_ubyte, crop
 from ._skeletonize_3d_cy import _compute_thin_image
 
 
@@ -46,24 +46,19 @@ def skeletonize_3d(img):
            Computer Vision, Graphics, and Image Processing, 56(6):462-478, 1994.
 
     """
-    # make sure the image is 3D or 2D (if it is, temporarily upcast to 3D)
+    # make sure the image is 3D or 2D
     if img.ndim < 2 or img.ndim > 3:
         raise ValueError('expect 2D, got ndim = %s' % img.ndim)
 
     img = np.ascontiguousarray(img)
     img = img_as_ubyte(img, force_copy=False)
 
-    # make an in image 3D pad w/ zeros to simplify dealing w/ boundaries
-    # NB: careful to not clobber the original *and* minimize copying
+    # make an in image 3D and pad it w/ zeros to simplify dealing w/ boundaries
+    # NB: careful here to not clobber the original *and* minimize copying
+    img_o = img
     if img.ndim == 2:
-
-        if img.shape[0] == 1 or img.shape[1] == 1:
-            # nothing to do, image is already thin. Bail out.
-            return img.copy()
-
-        img_o = np.pad(img[None, ...], pad_width=1, mode='constant')
-    else:
-        img_o = np.pad(img, pad_width=1, mode='constant')
+        img_o = img[np.newaxis, ...]
+    img_o = np.pad(img_o, pad_width=1, mode='constant')
 
     # normalize to binary
     maxval = img_o.max()
@@ -72,9 +67,10 @@ def skeletonize_3d(img):
     # do the computation
     img_o = np.asarray(_compute_thin_image(img_o))
 
-    # clip it back and restore the original intensity range
-    img_o = img_o[1:-1, 1:-1, 1:-1]
-    img_o = img_o.squeeze()
+    # crop it back and restore the original intensity range
+    img_o = crop(img_o, crop_width=1)
+    if img.ndim == 2:
+        img_o = img_o[0]
     img_o *= maxval
 
-    return img_o
+    return img_o
\ No newline at end of file
diff --git a/skimage/morphology/tests/test_skeletonize_3d.py b/skimage/morphology/tests/test_skeletonize_3d.py
index d373f0d5..d5859a5d 100644
--- a/skimage/morphology/tests/test_skeletonize_3d.py
+++ b/skimage/morphology/tests/test_skeletonize_3d.py
@@ -27,6 +27,13 @@ def test_skeletonize_wrong_dim():
     assert_raises(ValueError, skeletonize_3d, im)
 
 
+def test_skeletonize_1D():
+    # a corner case of an image of a shape(1, N)
+    im = np.ones((5, 1), dtype=np.uint8)
+    res = skeletonize_3d(im)
+    assert_equal(res, im)
+
+
 def test_skeletonize_no_foreground():
     im = np.zeros((5, 5), dtype=np.uint8)
     result = skeletonize_3d(im)
@@ -80,7 +87,8 @@ def test_input():
     # check that the input is not clobbered
     # for 2D and 3D images of varying dtypes
     imgs = [np.ones((8, 8), dtype=float), np.ones((4, 8, 8), dtype=float),
-            np.ones((8, 8), dtype=np.uint8), np.ones((4, 8, 8), dtype=np.uint8)]
+            np.ones((8, 8), dtype=np.uint8), np.ones((4, 8, 8), dtype=np.uint8),
+            np.ones((8, 8), dtype=bool), np.ones((4, 8, 8), dtype=bool)]
     for img in imgs:
         yield check_input, img