def test_flat_maxima(self):
"""Test if flat maxima are detected correctly."""
x = np.array([-1.3, 0, 1, 0, 2, 2, 0, 3, 3, 3, 2.99, 4, 4, 4, 4, -10,
-5, -5, -5, -5, -5, -10])
midpoints, left_edges, right_edges = _local_maxima_1d(x)
assert_equal(midpoints, np.array([2, 4, 8, 12, 18]))
assert_equal(left_edges, np.array([2, 4, 7, 11, 16]))
assert_equal(right_edges, np.array([2, 5, 9, 14, 20]))
def test_exceptions(self):
"""Test input validation and raised exceptions."""
with raises(ValueError, match="wrong number of dimensions"):
_local_maxima_1d(np.ones((1, 1)))
with raises(ValueError, match="expected 'float64_t'"):
_local_maxima_1d(np.ones(1, dtype=int))
with raises(TypeError, match="list"):
_local_maxima_1d([1., 2.])
with raises(TypeError, match="'x' must not be None"):
_local_maxima_1d(None)
def test_simple(self):
"""Test with simple signal."""
x = np.linspace(-10, 10, 50)
x[2::3] += 1
expected = np.arange(2, 50, 3)
for array in _local_maxima_1d(x):
# For plateaus of size 1, the edges are identical with the
# midpoints
assert_equal(array, expected)
assert_(array.base is None)
def test_simple(self):
"""Test with simple signal."""
x = np.linspace(-10, 10, 50)
x[2::3] += 1
expected = np.arange(2, 50, 3)
for array in _local_maxima_1d(x):
# For plateaus of size 1, the edges are identical with the
# midpoints
assert_equal(array, expected)
assert_(array.base is None)
def test_flat_maxima(self):
"""Test if flat maxima are detected correctly."""
x = np.array([
-1.3, 0, 1, 0, 2, 2, 0, 3, 3, 3, 2.99, 4, 4, 4, 4, -10, -5, -5, -5,
-5, -5, -10
])
midpoints, left_edges, right_edges = _local_maxima_1d(x)
assert_equal(midpoints, np.array([2, 4, 8, 12, 18]))
assert_equal(left_edges, np.array([2, 4, 7, 11, 16]))
assert_equal(right_edges, np.array([2, 5, 9, 14, 20]))
so = ctypes.CDLL('find_peak.so')
so.select_by_peak_distance.argtypes = (T.int_p, T.int, T.float_p, T.float,
T.bool_p)
so.select_by_peak_distance.restype = None
so.select_by_peak_distance(peaks, len(peaks_np), priority, distance, keep)
del (so)
return keep_np
from scipy.misc import electrocardiogram
x = electrocardiogram()[2000:4000]
from scipy.signal._peak_finding_utils import _local_maxima_1d
peaks, _, _ = _local_maxima_1d(x)
distance = 5
keep = select_by_peak_distance(peaks, x[peaks], distance)
from scipy.signal._peak_finding_utils import \
_select_by_peak_distance as scipy_select_by_peak_distance
keep_groundtrue = scipy_select_by_peak_distance(peaks, x[peaks], distance)
# print(np.argsort(x[peaks]))
print((keep))
print((keep_groundtrue))
print(((keep ^ keep_groundtrue)))
print(np.count_nonzero(keep))
def test_linear(self):
"""Test with linear signal."""
x = np.linspace(0, 100)
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
def test_empty(self):
"""Test with empty signal."""
x = np.array([], dtype=np.float64)
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
def test_signal_edges(self, x):
"""Test if behavior on signal edges is correct."""
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
def test_linear(self):
"""Test with linear signal."""
x = np.linspace(0, 100)
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
def test_empty(self):
"""Test with empty signal."""
x = np.array([], dtype=np.float64)
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
def test_signal_edges(self, x):
"""Test if behavior on signal edges is correct."""
for array in _local_maxima_1d(x):
assert_equal(array, np.array([]))
assert_(array.base is None)
