def test_spike_realdata(self):
"""
Test with real-world data.
"""
suspect_threshold = 0.5
fail_threshold = 1
arr = [
-0.189, -0.0792, -0.0122, 0.0457, 0.0671, 0.0213, -0.0488, -0.1463,
-0.2438, -0.3261, -0.3871, -0.4054, -0.3932, -0.3383, -0.2804,
-0.2347, -0.2134, -0.2347, -0.2926, -0.3597, -0.442, -0.509, 0,
-0.5944, -0.57, -0.4267, -0.2926, -0.1585, -0.0945, -0.0762
]
expected = [
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
3, 1, 1, 1, 1, 1, 1, 1
]
inputs = [
arr,
np.asarray(arr, dtype=np.floating),
dask_arr(np.asarray(arr, dtype=np.floating))
]
for i in inputs:
npt.assert_array_equal(
qartod.spike_test(inp=i,
suspect_threshold=suspect_threshold,
fail_threshold=fail_threshold), expected)
def test_spike_initial_final_values(self):
"""
The test is not defined for the initial and final values in the array
"""
arr = [-100, -99, -99, -98]
expected = [2, 1, 1, 2]
npt.assert_array_equal(
qartod.spike_test(inp=arr,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold), expected)
def test_spike_negative_vals(self):
"""
Test to make spike detection works properly for negative values.
"""
arr = [-10, -12, -999.99, -13, -15, -40, -9, -9]
# First and last elements should always be good data, unless someone
# has set a threshold to zero.
expected = [1, 4, 4, 4, 1, 3, 1, 1]
inputs = [
arr,
np.asarray(arr, dtype=np.floating),
dask_arr(np.asarray(arr, dtype=np.floating))
]
for i in inputs:
npt.assert_array_equal(
qartod.spike_test(inp=i,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold),
expected)
def test_spike(self):
"""
Test to make ensure single value spike detection works properly.
"""
arr = [10, 12, 999.99, 13, 15, 40, 9, 9]
# First and last elements should always be good data, unless someone
# has set a threshold to zero.
expected = [2, 4, 4, 4, 1, 3, 1, 2]
inputs = [
arr,
np.asarray(arr, dtype=np.float64),
dask_arr(np.asarray(arr, dtype=np.float64))
]
for i in inputs:
npt.assert_array_equal(
qartod.spike_test(inp=i,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold),
expected)
def test_spike_masked(self):
"""
Test with missing data.
"""
arr = [
10, 12, 999.99, 13, 15, 40, 9, 9, None, 10, 10, 999.99, 10, None
]
# First and last elements should always be good data, unless someone
# has set a threshold to zero.
expected = [1, 4, 4, 4, 1, 3, 1, 1, 9, 9, 4, 4, 4, 9]
inputs = [
arr,
np.asarray(arr, dtype=np.floating),
dask_arr(np.asarray(arr, dtype=np.floating))
]
for i in inputs:
npt.assert_array_equal(
qartod.spike_test(inp=i,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold),
expected)
