本文整理汇总了Python中skimage.feature.peak.peak_local_max函数的典型用法代码示例。如果您正苦于以下问题：Python peak_local_max函数的具体用法？Python peak_local_max怎么用？Python peak_local_max使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了peak_local_max函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_trivial_case
def test_trivial_case(self):
trivial = np.zeros((25, 25))
peak_indices = peak.peak_local_max(trivial, min_distance=1, indices=True)
assert type(peak_indices) is np.ndarray
assert not peak_indices # inherent boolean-ness of empty list
peaks = peak.peak_local_max(trivial, min_distance=1, indices=False)
assert (peaks.astype(np.bool) == trivial).all()示例2: test_trivial_case
def test_trivial_case(self):
trivial = np.zeros((25, 25))
peak_indices = peak.peak_local_max(trivial, min_distance=1, indices=True)
assert type(peak_indices) is np.ndarray
assert peak_indices.size == 0
peaks = peak.peak_local_max(trivial, min_distance=1, indices=False)
assert (peaks.astype(np.bool) == trivial).all()示例3: test_4D
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]])示例4: test_num_peaks
def test_num_peaks():
image = np.zeros((3, 7), dtype=np.uint8)
image[1, 1] = 10
image[1, 3] = 11
image[1, 5] = 12
assert len(peak.peak_local_max(image, min_distance=1)) == 3
peaks_limited = peak.peak_local_max(image, min_distance=1, num_peaks=2)
assert len(peaks_limited) == 2
assert (1, 3) in peaks_limited
assert (1, 5) in peaks_limited示例5: test_threshold_rel_default
def test_threshold_rel_default(self):
image = np.ones((5, 5))
image[2, 2] = 1
assert len(peak.peak_local_max(image)) == 0
image[2, 2] = 2
assert_equal(peak.peak_local_max(image), [[2, 2]])
image[2, 2] = 0
assert len(peak.peak_local_max(image, min_distance=0)) == image.size - 1示例6: test_sorted_peaks
def test_sorted_peaks(self):
image = np.zeros((5, 5), dtype=np.uint8)
image[1, 1] = 20
image[3, 3] = 10
peaks = peak.peak_local_max(image, min_distance=1)
assert peaks.tolist() == [[3, 3], [1, 1]]
image = np.zeros((3, 10))
image[1, (1, 3, 5, 7)] = (1, 3, 2, 4)
peaks = peak.peak_local_max(image, min_distance=1)
assert peaks.tolist() == [[1, 7], [1, 5], [1, 3], [1, 1]]示例7: test_disk
def test_disk():
'''regression test of img-1194, footprint = [1]
Test peak.peak_local_max when every point is a local maximum
'''
image = np.random.uniform(size=(10, 20))
footprint = np.array([[1]])
result = peak.peak_local_max(image, labels=np.ones((10, 20)),
footprint=footprint,
min_distance=1, threshold_rel=0,
indices=False, exclude_border=False)
assert np.all(result)
result = peak.peak_local_max(image, footprint=footprint)
assert np.all(result)示例8: test_3D
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, min_distance=10, threshold_rel=0),
[[15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=6, threshold_rel=0),
[[15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=10, threshold_rel=0,
exclude_border=False),
[[5, 5, 5], [15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=5, threshold_rel=0),
[[5, 5, 5], [15, 15, 15]])示例9: test_4D
def test_4D(self):
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, min_distance=10, threshold_rel=0),
[[15, 15, 15, 15]])
assert_equal(peak.peak_local_max(image, min_distance=6, threshold_rel=0),
[[15, 15, 15, 15]])
assert sorted(peak.peak_local_max(image, min_distance=10, threshold_rel=0,
exclude_border=False).tolist()) == \
[[5, 5, 5, 5], [15, 15, 15, 15]]
assert sorted(peak.peak_local_max(image, min_distance=5,
threshold_rel=0).tolist()) == \
[[5, 5, 5, 5], [15, 15, 15, 15]]示例10: test_num_peaks_and_labels
def test_num_peaks_and_labels(self):
image = np.zeros((7, 7), dtype=np.uint8)
labels = np.zeros((7, 7), dtype=np.uint8) + 20
image[1, 1] = 10
image[1, 3] = 11
image[1, 5] = 12
image[3, 5] = 8
image[5, 3] = 7
peaks_limited = peak.peak_local_max(
image, min_distance=1, threshold_abs=0, labels=labels)
assert len(peaks_limited) == 5
peaks_limited = peak.peak_local_max(
image, min_distance=1, threshold_abs=0, labels=labels, num_peaks=2)
assert len(peaks_limited) == 2示例11: test_adjacent_and_different
def test_adjacent_and_different(self):
image = np.zeros((10, 20))
labels = np.zeros((10, 20), int)
image[5, 5] = 1
image[5, 6] = .5
labels[5, 5:6] = 1
expected = (image == 1)
result = peak.peak_local_max(image, labels=labels,
footprint=np.ones((3, 3), bool),
min_distance=1, threshold_rel=0,
indices=False, exclude_border=False)
assert np.all(result == expected)
result = peak.peak_local_max(image, labels=labels,
min_distance=1, threshold_rel=0,
indices=False, exclude_border=False)
assert np.all(result == expected)示例12: test_num_peaks3D
def test_num_peaks3D(self):
# 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示例13: test_relative_threshold
def test_relative_threshold(self):
image = np.zeros((5, 5), dtype=np.uint8)
image[1, 1] = 10
image[3, 3] = 20
peaks = peak.peak_local_max(image, min_distance=1, threshold_rel=0.5)
assert len(peaks) == 1
assert_array_almost_equal(peaks, [(3, 3)])示例14: test_absolute_threshold
def test_absolute_threshold(self):
image = np.zeros((5, 5), dtype=np.uint8)
image[1, 1] = 10
image[3, 3] = 20
peaks = peak.peak_local_max(image, min_distance=1, threshold_abs=10)
assert len(peaks) == 1
assert_close(peaks, [(3, 3)])示例15: test_empty
def test_empty(self):
image = np.zeros((10, 20))
labels = np.zeros((10, 20), int)
result = peak.peak_local_max(image, labels=labels,
footprint=np.ones((3, 3), bool),
min_distance=1, threshold_rel=0,
indices=False, exclude_border=False)
assert np.all(~ result)