def test_distance_condition(self):
"""
Test distance condition for peaks.
"""
# Peaks of different height with constant distance 3
peaks_all = np.arange(1, 21, 3)
x = np.zeros(21)
x[peaks_all] += np.linspace(1, 2, peaks_all.size)
# Test if peaks with "minimal" distance are still selected (distance = 3)
assert_equal(find_peaks(x, distance=3)[0], peaks_all)
# Select every second peak (distance > 3)
peaks_subset = find_peaks(x, distance=3.0001)[0]
# Test if peaks_subset is subset of peaks_all
assert_(
np.setdiff1d(peaks_subset, peaks_all, assume_unique=True).size == 0
)
# Test if every second peak was removed
assert_equal(np.diff(peaks_subset), 6)
# Test priority of peak removal
x = [-2, 1, -1, 0, -3]
peaks_subset = find_peaks(x, distance=10)[0] # use distance > x size
assert_(peaks_subset.size == 1 and peaks_subset[0] == 1)
def test_distance_condition(self):
"""
Test distance condition for peaks.
"""
# Peaks of different height with constant distance 3
peaks_all = np.arange(1, 21, 3)
x = np.zeros(21)
x[peaks_all] += np.linspace(1, 2, peaks_all.size)
# Test if peaks with "minimal" distance are still selected (distance = 3)
assert_equal(find_peaks(x, distance=3)[0], peaks_all)
# Select every second peak (distance > 3)
peaks_subset = find_peaks(x, distance=3.0001)[0]
# Test if peaks_subset is subset of peaks_all
assert_(
np.setdiff1d(peaks_subset, peaks_all, assume_unique=True).size ==
0)
# Test if every second peak was removed
assert_equal(np.diff(peaks_subset), 6)
# Test priority of peak removal
x = [-2, 1, -1, 0, -3]
peaks_subset = find_peaks(x, distance=10)[0] # use distance > x size
assert_(peaks_subset.size == 1 and peaks_subset[0] == 1)
def test_height_condition(self):
"""
Test height condition for peaks.
"""
x = (0., 1/3, 0., 2.5, 0, 4., 0)
peaks, props = find_peaks(x, height=(None, None))
assert_equal(peaks, np.array([1, 3, 5]))
assert_equal(props['peak_heights'], np.array([1/3, 2.5, 4.]))
assert_equal(find_peaks(x, height=0.5)[0], np.array([3, 5]))
assert_equal(find_peaks(x, height=(None, 3))[0], np.array([1, 3]))
assert_equal(find_peaks(x, height=(2, 3))[0], np.array([3]))
def test_height_condition(self):
"""
Test height condition for peaks.
"""
x = (0., 1 / 3, 0., 2.5, 0, 4., 0)
peaks, props = find_peaks(x, height=(None, None))
assert_equal(peaks, np.array([1, 3, 5]))
assert_equal(props['peak_heights'], np.array([1 / 3, 2.5, 4.]))
assert_equal(find_peaks(x, height=0.5)[0], np.array([3, 5]))
assert_equal(find_peaks(x, height=(None, 3))[0], np.array([1, 3]))
assert_equal(find_peaks(x, height=(2, 3))[0], np.array([3]))
def test_readonly_array(self, kwargs):
"""
Test readonly arrays are accepted.
"""
x = np.linspace(0, 10, 15)
x_readonly = x.copy()
x_readonly.flags.writeable = False
peaks, _ = find_peaks(x)
peaks_readonly, _ = find_peaks(x_readonly, **kwargs)
assert_allclose(peaks, peaks_readonly)
def test_constant(self):
"""
Test behavior for signal without local maxima.
"""
open_interval = (None, None)
peaks, props = find_peaks(np.ones(10),
height=open_interval, threshold=open_interval,
prominence=open_interval, width=open_interval)
assert_(peaks.size == 0)
for key in self.property_keys:
assert_(props[key].size == 0)
def test_constant(self):
"""
Test behavior for signal without local maxima.
"""
open_interval = (None, None)
peaks, props = find_peaks(np.ones(10),
height=open_interval, threshold=open_interval,
prominence=open_interval, width=open_interval)
assert_(peaks.size == 0)
for key in self.property_keys:
assert_(props[key].size == 0)
def test_width_condition(self):
"""
Test width condition for peaks.
"""
x = np.array([1, 0, 1, 2, 1, 0, -1, 4, 0])
peaks, props = find_peaks(x, width=(None, 2), rel_height=0.75)
assert_(peaks.size == 1)
assert_(peaks == 7)
assert_(props['widths'] == 1.35)
assert_(props['width_heights'] == 1.)
assert_(props['left_ips'] == 6.4)
assert_(props['right_ips'] == 7.75)
def test_width_condition(self):
"""
Test width condition for peaks.
"""
x = np.array([1, 0, 1, 2, 1, 0, -1, 4, 0])
peaks, props = find_peaks(x, width=(None, 2), rel_height=0.75)
assert_equal(peaks.size, 1)
assert_equal(peaks, 7)
assert_allclose(props['widths'], 1.35)
assert_allclose(props['width_heights'], 1.)
assert_allclose(props['left_ips'], 6.4)
assert_allclose(props['right_ips'], 7.75)
def test_width_condition(self):
"""
Test width condition for peaks.
"""
x = np.array([1, 0, 1, 2, 1, 0, -1, 4, 0])
peaks, props = find_peaks(x, width=(None, 2), rel_height=0.75)
assert_equal(peaks.size, 1)
assert_equal(peaks, 7)
assert_allclose(props['widths'], 1.35)
assert_allclose(props['width_heights'], 1.)
assert_allclose(props['left_ips'], 6.4)
assert_allclose(props['right_ips'], 7.75)
def test_properties(self):
"""
Test returned properties.
"""
open_interval = (None, None)
x = [0, 1, 0, 2, 1.5, 0, 3, 0, 5, 9]
peaks, props = find_peaks(x,
height=open_interval, threshold=open_interval,
prominence=open_interval, width=open_interval)
assert_(len(props) == len(self.property_keys))
for key in self.property_keys:
assert_(peaks.size == props[key].size)
def test_properties(self):
"""
Test returned properties.
"""
open_interval = (None, None)
x = [0, 1, 0, 2, 1.5, 0, 3, 0, 5, 9]
peaks, props = find_peaks(x,
height=open_interval, threshold=open_interval,
prominence=open_interval, width=open_interval)
assert_(len(props) == len(self.property_keys))
for key in self.property_keys:
assert_(peaks.size == props[key].size)
def test_width_condition(self):
"""
Test width condition for peaks.
"""
x = np.array([1, 0, 1, 2, 1, 0, -1, 4, 0])
peaks, props = find_peaks(x, width=(None, 2), rel_height=0.75)
assert_(peaks.size == 1)
assert_(peaks == 7)
assert_(props['widths'] == 1.35)
assert_(props['width_heights'] == 1.)
assert_(props['left_ips'] == 6.4)
assert_(props['right_ips'] == 7.75)
def test_plateau_size(self):
"""
Test plateau size condition for peaks.
"""
# Prepare signal with peaks with peak_height == plateau_size
plateau_sizes = np.array([1, 2, 3, 4, 8, 20, 111])
x = np.zeros(plateau_sizes.size * 2 + 1)
x[1::2] = plateau_sizes
repeats = np.ones(x.size, dtype=int)
repeats[1::2] = x[1::2]
x = np.repeat(x, repeats)
# Test full output
peaks, props = find_peaks(x, plateau_size=(None, None))
assert_equal(peaks, [1, 3, 7, 11, 18, 33, 100])
assert_equal(props["plateau_sizes"], plateau_sizes)
assert_equal(props["left_edges"], peaks - (plateau_sizes - 1) // 2)
assert_equal(props["right_edges"], peaks + plateau_sizes // 2)
# Test conditions
assert_equal(find_peaks(x, plateau_size=4)[0], [11, 18, 33, 100])
assert_equal(find_peaks(x, plateau_size=(None, 3.5))[0], [1, 3, 7])
assert_equal(find_peaks(x, plateau_size=(5, 50))[0], [18, 33])
def test_plateau_size(self):
"""
Test plateau size condition for peaks.
"""
# Prepare signal with peaks with peak_height == plateau_size
plateau_sizes = np.array([1, 2, 3, 4, 8, 20, 111])
x = np.zeros(plateau_sizes.size * 2 + 1)
x[1::2] = plateau_sizes
repeats = np.ones(x.size, dtype=int)
repeats[1::2] = x[1::2]
x = np.repeat(x, repeats)
# Test full output
peaks, props = find_peaks(x, plateau_size=(None, None))
assert_equal(peaks, [1, 3, 7, 11, 18, 33, 100])
assert_equal(props["plateau_sizes"], plateau_sizes)
assert_equal(props["left_edges"], peaks - (plateau_sizes - 1) // 2)
assert_equal(props["right_edges"], peaks + plateau_sizes // 2)
# Test conditions
assert_equal(find_peaks(x, plateau_size=4)[0], [11, 18, 33, 100])
assert_equal(find_peaks(x, plateau_size=(None, 3.5))[0], [1, 3, 7])
assert_equal(find_peaks(x, plateau_size=(5, 50))[0], [18, 33])
def test_wlen_smaller_plateau(self):
"""
Test behavior of prominence and width calculation if the given window
length is smaller than a peak's plateau size.
Regression test for gh-9110.
"""
peaks, props = find_peaks([0, 1, 1, 1, 0], prominence=(None, None),
width=(None, None), wlen=2)
assert_equal(peaks, 2)
assert_equal(props["prominences"], 0)
assert_equal(props["widths"], 0)
assert_equal(props["width_heights"], 1)
for key in ("left_bases", "right_bases", "left_ips", "right_ips"):
assert_equal(props[key], peaks)
def test_wlen_smaller_plateau(self):
"""
Test behavior of prominence and width calculation if the given window
length is smaller than a peak's plateau size.
Regression test for gh-9110.
"""
peaks, props = find_peaks([0, 1, 1, 1, 0], prominence=(None, None),
width=(None, None), wlen=2)
assert_equal(peaks, 2)
assert_equal(props["prominences"], 0)
assert_equal(props["widths"], 0)
assert_equal(props["width_heights"], 1)
for key in ("left_bases", "right_bases", "left_ips", "right_ips"):
assert_equal(props[key], peaks)
def test_raises(self):
"""
Test exceptions raised by function.
"""
with raises(ValueError, match="dimension"):
find_peaks(np.array(1))
with raises(ValueError, match="dimension"):
find_peaks(np.ones((2, 2)))
with raises(ValueError, match="distance"):
find_peaks(np.arange(10), distance=-1)
def test_raises(self):
"""
Test exceptions raised by function.
"""
with raises(ValueError, match="1-D array"):
find_peaks(np.array(1))
with raises(ValueError, match="1-D array"):
find_peaks(np.ones((2, 2)))
with raises(ValueError, match="distance"):
find_peaks(np.arange(10), distance=-1)
def test_prominence_condition(self):
"""
Test prominence condition for peaks.
"""
x = np.linspace(0, 10, 100)
peaks_true = np.arange(1, 99, 2)
offset = np.linspace(1, 10, peaks_true.size)
x[peaks_true] += offset
prominences = x[peaks_true] - x[peaks_true + 1]
interval = (3, 9)
keep = np.nonzero(
(interval[0] <= prominences) & (prominences <= interval[1]))
peaks_calc, properties = find_peaks(x, prominence=interval)
assert_equal(peaks_calc, peaks_true[keep])
assert_equal(properties['prominences'], prominences[keep])
assert_equal(properties['left_bases'], 0)
assert_equal(properties['right_bases'], peaks_true[keep] + 1)
def test_prominence_condition(self):
"""
Test prominence condition for peaks.
"""
x = np.linspace(0, 10, 100)
peaks_true = np.arange(1, 99, 2)
offset = np.linspace(1, 10, peaks_true.size)
x[peaks_true] += offset
prominences = x[peaks_true] - x[peaks_true + 1]
interval = (3, 9)
keep = np.nonzero((interval[0] <= prominences)
& (prominences <= interval[1]))
peaks_calc, properties = find_peaks(x, prominence=interval)
assert_equal(peaks_calc, peaks_true[keep])
assert_equal(properties['prominences'], prominences[keep])
assert_equal(properties['left_bases'], 0)
assert_equal(properties['right_bases'], peaks_true[keep] + 1)
def test_threshold_condition(self):
"""
Test threshold condition for peaks.
"""
x = (0, 2, 1, 4, -1)
peaks, props = find_peaks(x, threshold=(None, None))
assert_equal(peaks, np.array([1, 3]))
assert_equal(props['left_thresholds'], np.array([2, 3]))
assert_equal(props['right_thresholds'], np.array([1, 5]))
assert_equal(find_peaks(x, threshold=2)[0], np.array([3]))
assert_equal(find_peaks(x, threshold=3.5)[0], np.array([]))
assert_equal(find_peaks(x, threshold=(None, 5))[0], np.array([1, 3]))
assert_equal(find_peaks(x, threshold=(None, 4))[0], np.array([1]))
assert_equal(find_peaks(x, threshold=(2, 4))[0], np.array([]))
def test_threshold_condition(self):
"""
Test threshold condition for peaks.
"""
x = (0, 2, 1, 4, -1)
peaks, props = find_peaks(x, threshold=(None, None))
assert_equal(peaks, np.array([1, 3]))
assert_equal(props['left_thresholds'], np.array([2, 3]))
assert_equal(props['right_thresholds'], np.array([1, 5]))
assert_equal(find_peaks(x, threshold=2)[0], np.array([3]))
assert_equal(find_peaks(x, threshold=3.5)[0], np.array([]))
assert_equal(find_peaks(x, threshold=(None, 5))[0], np.array([1, 3]))
assert_equal(find_peaks(x, threshold=(None, 4))[0], np.array([1]))
assert_equal(find_peaks(x, threshold=(2, 4))[0], np.array([]))