Merge pull request #1355 from kevin-keraudren/peak_local_max-NDarrays-issue1354

ENH: Full ndarray support for peak_local_max

CONTRIBUTORS.txt

@@ -202,4 +202,7 @@
   Extended the image labelling implementation so it also works on 3D images.
 
 - Salvatore Scaramuzzino
-  RectTool example
+  RectTool example
+
+- Kevin Keraudren
+  Fix and test for feature.peak_local_max

skimage/feature/peak.py

@@ -146,10 +146,10 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
     peak_threshold = max(np.max(image.ravel()) * threshold_rel, threshold_abs)
 
     # get coordinates of peaks
-    coordinates = np.transpose((image > peak_threshold).nonzero())
+    coordinates = np.argwhere(image > peak_threshold)
 
     if coordinates.shape[0] > num_peaks:
-        intensities = image[coordinates[:, 0], coordinates[:, 1]]
+        intensities = image.flat[np.ravel_multi_index(coordinates.transpose(),image.shape)]
         idx_maxsort = np.argsort(intensities)[::-1]
         coordinates = coordinates[idx_maxsort][:num_peaks]
 

skimage/feature/tests/test_peak.py

@@ -82,6 +82,15 @@ def test_num_peaks():
     assert (3, 5) in peaks_limited
 
 
+def test_num_peaks3D():
+    # Issue 1354: the old code only hold for 2D arrays
+    # and this code would die with IndexError
+    image = np.zeros((10, 10, 100))
+    image[5,5,::5] = np.arange(20)
+    peaks_limited = peak.peak_local_max(image, min_distance=1, num_peaks=2)
+    assert len(peaks_limited) == 2
+    
+
 def test_reorder_labels():
     image = np.random.uniform(size=(40, 60))
     i, j = np.mgrid[0:40, 0:60]