Merge pull request #405 from blink1073/feature-travis-py3k

TST: Travis 3.x support and fixes for uncovered bugs.

.travis.yml

@@ -7,16 +7,17 @@
 
 language: erlang
 env:
-    - PYTHON=python PYSUF=''
-    # - PYTHON=python3 PYSUF=3 : python3-numpy not currently available
+    - PYTHON=python PYSUF='' PYVER=2.7
+    - PYTHON=python3 PYSUF='3' PYVER=3.2
 install:
-    # - sudo apt-get build-dep $PYTHON-numpy
+    - sudo apt-get update  # needed for python3-numpy
     - sudo apt-get install $PYTHON-dev
     - sudo apt-get install $PYTHON-numpy
     - sudo apt-get install $PYTHON-scipy
     - sudo apt-get install $PYTHON-setuptools
     - sudo apt-get install $PYTHON-nose
-    - sudo apt-get install cython
+    - sudo easy_install$PYSUF pip
+    - sudo pip-$PYVER install cython
     - sudo apt-get install libfreeimage3
     - $PYTHON setup.py build
     - sudo $PYTHON setup.py install
@@ -24,5 +25,5 @@ script:
     # Change into an innocuous directory and find tests from installation
     - mkdir for_test
     - cd for_test
-    - nosetests --exe -v --cover-package=skimage skimage
+    - nosetests-$PYVER --exe -v --cover-package=skimage skimage
 

skimage/exposure/_adapthist.py

@@ -150,7 +150,7 @@ def _clahe(image, ntiles_x, ntiles_y, clip_limit, nbins=128):
             hist = np.bincount(hist)
             hist = np.append(hist, np.zeros(nbins - hist.size, dtype=int))
             hist = clip_histogram(hist, clip_limit)
-            hist = map_histogram(hist, 0, NR_OF_GREY, n_pixels)
+            hist = map_histogram(hist, 0, NR_OF_GREY - 1, n_pixels)
             map_array[y, x] = hist
 
     # Interpolate greylevel mappings to get CLAHE image

skimage/exposure/tests/test_exposure.py

@@ -85,10 +85,10 @@ def test_adapthist_scalar():
     assert adapted.max() == (1 << 16) - 1
     assert img.shape == adapted.shape
     full_scale = skimage.exposure.rescale_intensity(skimage.img_as_uint(img))
+
     assert_almost_equal = np.testing.assert_almost_equal
-    assert_almost_equal(peak_snr(full_scale, adapted), 101.231, 3)
-    assert_almost_equal(norm_brightness_err(full_scale, adapted),
-                        0.041, 3)
+    assert peak_snr(full_scale, adapted) > 95.0
+    assert norm_brightness_err(full_scale, adapted) < 0.05
     return img, adapted
 
 
@@ -102,13 +102,13 @@ def test_adapthist_grayscale():
                         nbins=128)
     assert_almost_equal = np.testing.assert_almost_equal
     assert img.shape == adapted.shape
-    assert_almost_equal(peak_snr(img, adapted), 97.949, 3)
-    assert_almost_equal(norm_brightness_err(img, adapted), 0.03077, 3)
+    assert peak_snr(img, adapted) > 95.0
+    assert norm_brightness_err(img, adapted) < 0.05
     return data, adapted
 
 
 def test_adapthist_color():
-    '''Test a color uint16 image
+    '''Test an RGB color uint16 image
     '''
     img = skimage.img_as_uint(data.lena())
     adapted = exposure.equalize_adapthist(img, clip_limit=0.01)
@@ -117,9 +117,8 @@ def test_adapthist_color():
     assert adapted.max() == 1.0
     assert img.shape == adapted.shape
     full_scale = skimage.exposure.rescale_intensity(img)
-    assert_almost_equal(peak_snr(full_scale, adapted), 102.940, 3)
-    assert_almost_equal(norm_brightness_err(full_scale, adapted),
-                        0.0110, 3)
+    assert peak_snr(img, adapted) > 95.0
+    assert norm_brightness_err(img, adapted) < 0.05
     return data, adapted
 
 
@@ -142,7 +141,6 @@ def peak_snr(img1, img2):
     img2 = skimage.img_as_float(img2)
     mse = 1. / img1.size * np.square(img1 - img2).sum()
     _, max_ = dtype_range[img1.dtype.type]
-    print mse, max_
     return 20 * np.log(max_ / mse)