def test_flat_line(self):
arr = [
1, 2, 2.0001, 2, 2.0001, 2, 2.0001, 2, 4, 5, 3, 3.0001, 3.0005,
3.00001
]
expected = [1, 1, 1, 1, 3, 3, 4, 4, 1, 1, 1, 1, 1, 3]
inputs = [
arr,
np.asarray(arr, dtype=np.floating),
dask_arr(np.asarray(arr, dtype=np.floating))
]
for i in inputs:
result = qartod.flat_line_test(
inp=i,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance)
npt.assert_array_equal(result, expected)
# test epoch secs - should return same result
npt.assert_array_equal(
qartod.flat_line_test(inp=arr,
tinp=self.times_epoch_secs,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance), expected)
# test negative array - should return same result
arr = [-1 * x for x in arr]
npt.assert_array_equal(
qartod.flat_line_test(inp=arr,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance), expected)
# test empty array - should return empty result
arr = np.array([])
expected = np.array([])
npt.assert_array_equal(
qartod.flat_line_test(inp=arr,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance), expected)
# test nothing fails
arr = np.random.random(len(self.times))
expected = np.ones_like(arr)
npt.assert_array_equal(
qartod.flat_line_test(inp=arr,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=0.00000000001), expected)
def check(time, arr, expected):
result = qartod.flat_line_test(inp=arr,
tinp=time,
suspect_threshold=3,
fail_threshold=5,
tolerance=0.1)
npt.assert_array_equal(result, expected)
def test_flat_line_with_spike(self):
tolerance = 4
suspect_threshold = 3
fail_threshold = 6
time = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
arr = [1, 1, 1, 1, 1, 6, 5, 4, 3, 2]
expected = [1, 1, 1, 3, 3, 1, 1, 1, 3, 3]
result = qartod.flat_line_test(inp=arr,
tinp=time,
suspect_threshold=suspect_threshold,
fail_threshold=fail_threshold,
tolerance=tolerance)
npt.assert_array_equal(result, expected)
def test_flat_line_missing_values(self):
arr = [
1, None, np.ma.masked, 2, 2.0001, 2, 2.0001, 2, 4, None, 3, None,
None, 3.00001
]
expected = [1, 9, 9, 1, 3, 3, 4, 4, 1, 9, 1, 9, 9, 3]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
inputs = [
arr,
np.asarray(arr, dtype=np.floating),
dask_arr(np.asarray(arr, dtype=np.floating))
]
for i in inputs:
result = qartod.flat_line_test(
inp=i,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance)
npt.assert_array_equal(result, expected)
def test_flat_line_starting_from_beginning(self):
arr = [
2, 2.0001, 2, 2.0001, 2, 2.0001, 2, 4, 5, 3, 3.0001, 3.0005,
3.00001
]
expected = [1, 1, 1, 3, 3, 4, 4, 1, 1, 1, 1, 1, 3]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
inputs = [
arr,
np.asarray(arr, dtype=np.float64),
dask_arr(np.asarray(arr, dtype=np.float64))
]
for i in inputs:
result = qartod.flat_line_test(
inp=i,
tinp=self.times,
suspect_threshold=self.suspect_threshold,
fail_threshold=self.fail_threshold,
tolerance=self.tolerance)
npt.assert_array_equal(result, expected)
