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Merge pull request #906 from ahojnnes/peak-fix

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`peak_local_max`: fix docstring, add N-d tests
This commit is contained in:
Stefan van der Walt
2014-03-10 15:51:21 +02:00
parent ddfb17d3f7 cd13361b11
commit 941a252257
2 changed files with 39 additions and 9 deletions
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skimage/feature/peak.py
+13 -8
View File
@@ -49,9 +49,9 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
Returns
-------
output : (N, 2) array or ndarray of bools
output : ndarray or ndarray of bools
* If `indices = True` : (row, column) coordinates of peaks.
* If `indices = True` : (row, column, ...) coordinates of peaks.
* If `indices = False` : Boolean array shaped like `image`, with peaks
represented by True values.
@@ -65,10 +65,10 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
Examples
--------
>>> im = np.zeros((7, 7))
>>> im[3, 4] = 1
>>> im[3, 2] = 1.5
>>> im
>>> img1 = np.zeros((7, 7))
>>> img1[3, 4] = 1
>>> img1[3, 2] = 1.5
>>> img1
array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. , 0. ],
@@ -77,13 +77,18 @@ def peak_local_max(image, min_distance=10, threshold_abs=0, threshold_rel=0.1,
[ 0. , 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. , 0. ]])
>>> peak_local_max(im, min_distance=1)
>>> peak_local_max(img1, min_distance=1)
array([[3, 2],
[3, 4]])
>>> peak_local_max(im, min_distance=2)
>>> peak_local_max(img1, min_distance=2)
array([[3, 2]])
>>> img2 = np.zeros((20, 20, 20))
>>> img2[10, 10, 10] = 1
>>> peak_local_max(img2, exclude_border=False)
array([[10, 10, 10]])
"""
out = np.zeros_like(image, dtype=np.bool)
# In the case of labels, recursively build and return an output
skimage/feature/tests/test_peak.py
+26 -1
View File
@@ -1,5 +1,6 @@
import numpy as np
from numpy.testing import assert_array_almost_equal as assert_close
from numpy.testing import (assert_array_almost_equal as assert_close,
assert_equal)
import scipy.ndimage
from skimage.feature import peak
@@ -266,6 +267,30 @@ def test_disk():
assert np.all(result)
def test_3D():
image = np.zeros((30, 30, 30))
image[15, 15, 15] = 1
image[5, 5, 5] = 1
assert_equal(peak.peak_local_max(image), [[15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=6), [[15, 15, 15]])
assert_equal(peak.peak_local_max(image, exclude_border=False),
[[5, 5, 5], [15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=5),
[[5, 5, 5], [15, 15, 15]])
def test_4D():
image = np.zeros((30, 30, 30, 30))
image[15, 15, 15, 15] = 1
image[5, 5, 5, 5] = 1
assert_equal(peak.peak_local_max(image), [[15, 15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=6), [[15, 15, 15, 15]])
assert_equal(peak.peak_local_max(image, exclude_border=False),
[[5, 5, 5, 5], [15, 15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=5),
[[5, 5, 5, 5], [15, 15, 15, 15]])
if __name__ == '__main__':
from numpy import testing
testing.run_module_suite()