From 6586d1eb3fd01367cad5b73b0430a2a9bcfe23c7 Mon Sep 17 00:00:00 2001
From: Juan Nunez-Iglesias <juan.n@unimelb.edu.au>
Date: Mon, 12 Jan 2015 15:31:56 +1100
Subject: [PATCH] Test subpixel mark_boundaries

---
 skimage/segmentation/tests/test_boundaries.py | 33 +++++++++++++++++--
 1 file changed, 30 insertions(+), 3 deletions(-)

diff --git a/skimage/segmentation/tests/test_boundaries.py b/skimage/segmentation/tests/test_boundaries.py
index 4019e112..7b837f4e 100644
--- a/skimage/segmentation/tests/test_boundaries.py
+++ b/skimage/segmentation/tests/test_boundaries.py
@@ -1,8 +1,11 @@
 import numpy as np
-from numpy.testing import assert_array_equal
+from numpy.testing import assert_array_equal, assert_allclose
 from skimage.segmentation import find_boundaries, mark_boundaries
 
 
+white = (1, 1, 1)
+
+
 def test_find_boundaries():
     image = np.zeros((10, 10), dtype=np.uint8)
     image[2:7, 2:7] = 1
@@ -38,7 +41,7 @@ def test_mark_boundaries():
                     [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                     [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
 
-    result = mark_boundaries(image, label_image, color=(1, 1, 1)).mean(axis=2)
+    result = mark_boundaries(image, label_image, color=white).mean(axis=2)
     assert_array_equal(result, ref)
 
     ref = np.array([[0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
@@ -51,10 +54,34 @@ def test_mark_boundaries():
                     [2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
                     [0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
                     [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
-    result = mark_boundaries(image, label_image, color=(1, 1, 1),
+    result = mark_boundaries(image, label_image, color=white,
                              outline_color=(2, 2, 2)).mean(axis=2)
     assert_array_equal(result, ref)
 
 
+def test_mark_boundaries_subpixel():
+    labels = np.array([[0, 0, 0, 0],
+                       [0, 0, 5, 0],
+                       [0, 1, 5, 0],
+                       [0, 0, 5, 0],
+                       [0, 0, 0, 0]], dtype=np.uint8)
+    np.random.seed(0)
+    image = np.round(np.random.rand(*labels.shape), 2)
+    marked = np.mark_boundaries(image, labels, color=white, mode='subpixel')
+    marked_proj = np.round(np.mean(marked, axis=-1), 2)
+
+    ref_result = np.array(
+            [[ 0.55,  0.63,  0.72,  0.69,  0.6 ,  0.55,  0.54],
+             [ 0.45,  0.58,  0.72,  1.  ,  1.  ,  1.  ,  0.69],
+             [ 0.42,  0.54,  0.65,  1.  ,  0.44,  1.  ,  0.89],
+             [ 0.69,  1.  ,  1.  ,  1.  ,  0.69,  1.  ,  0.83],
+             [ 0.96,  1.  ,  0.38,  1.  ,  0.79,  1.  ,  0.53],
+             [ 0.89,  1.  ,  1.  ,  1.  ,  0.38,  1.  ,  0.16],
+             [ 0.57,  0.78,  0.93,  1.  ,  0.07,  1.  ,  0.09],
+             [ 0.2 ,  0.52,  0.92,  1.  ,  1.  ,  1.  ,  0.54],
+             [ 0.02,  0.35,  0.83,  0.9 ,  0.78,  0.81,  0.87]])
+    assert_allclose(marked_proj, ref_result, atol=0.01)
+
+
 if __name__ == "__main__":
     np.testing.run_module_suite()