FIX: util.montage2d 'normalize' becomes 'rescale_intensity' and defaults to False

skimage/util/montage.py

@@ -1,11 +1,12 @@
 __all__ = ['montage2d']
 
 import numpy as np
+from .. import exposure
 
 EPSILON = 1e-6
 
 
-def montage2d(arr_in, fill='mean', normalize=True):
+def montage2d(arr_in, fill='mean', rescale_intensity=False):
     """Create a 2-dimensional 'montage' from a 3-dimensional input array
     representing an ensemble of equally shaped 2-dimensional images.
 
@@ -35,8 +36,8 @@ def montage2d(arr_in, fill='mean', normalize=True):
         How to fill the 2-dimensional output array when sqrt(n_images)
         is not an integer. If 'mean' is chosen, then fill = arr_in.mean().
 
-    normalize: bool, optional
-        Whether to normalize each image with zero-mean, unit-variance.
+    rescale_intensity: bool, optional
+        Whether to rescale the intensity of each image to [0, 1].
 
     Returns
     -------
@@ -73,14 +74,11 @@ def montage2d(arr_in, fill='mean', normalize=True):
 
     n_images, height, width = arr_in.shape
 
-    # -- normalize if necessary
-    if normalize:
-        arr_in = arr_in.T
-        arr_in -= arr_in.mean(0)
-        astd = arr_in.std(0)
-        astd[astd < EPSILON] = 1
-        arr_in /= astd
-        arr_in = arr_in.T
+    # -- rescale intensity if necessary
+    if rescale_intensity:
+        for i in xrange(n_images):
+            arr_in[i] = exposure.rescale_intensity(
+                arr_in[i], out_range=(0.0, 1.0))
 
     # -- determine alpha
     alpha = int(np.ceil(np.sqrt(n_images)))

skimage/util/tests/test_montage.py

@@ -53,6 +53,28 @@ def test_shape():
     assert_equal(arr_out.shape, (alpha * height, alpha * width))
 
 
+def test_rescale_intensity():
+    n_images = 4
+    height, width = 3, 3
+    arr_in = np.arange(n_images * height * width, dtype=np.float32)
+    arr_in = arr_in.reshape(n_images, height, width)
+
+    arr_out = montage2d(arr_in, rescale_intensity=True)
+
+    gt = np.array(
+        [[ 0.   ,  0.125,  0.25 ,  0.   ,  0.125,  0.25 ],
+         [ 0.375,  0.5  ,  0.625,  0.375,  0.5  ,  0.625],
+         [ 0.75 ,  0.875,  1.   ,  0.75 ,  0.875,  1.   ],
+         [ 0.   ,  0.125,  0.25 ,  0.   ,  0.125,  0.25 ],
+         [ 0.375,  0.5  ,  0.625,  0.375,  0.5  ,  0.625],
+         [ 0.75 ,  0.875,  1.   ,  0.75 ,  0.875,  1.   ]]
+        )
+
+    assert_equal(arr_out.min(), 0.0)
+    assert_equal(arr_out.max(), 1.0)
+    assert_array_equal(arr_out, gt)
+
+
 @raises(AssertionError)
 def test_error_ndim():
     arr_error = np.random.randn(1, 2, 3, 4)