def test_dataqc_spiketest_extended(self):
dat = [-1 , 3 , 40 , -1 , 1 , -6 , -6 , 1 , 2 , 4 , 3 , 1 , -1 , 40 , 1 , 1 , 4 , 2 , 2 , 2 , 1 , 2 , 100]
out = [ 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 0 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 0]
acc = 0.1
N = 5
L = 7
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
dat = np.arange(20)
dat[0] = 100 # spike at the beginning
dat[10] = 100 # spike in the middle
dat[19] = 100 # spike at the end
out = np.empty(20, dtype=np.int8)
out.fill(1)
out[0] = 0
out[10] = 0
out[19] = 0
acc = 0.1
N = 5
L = 7 # longer smooothing
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
def test_dataqc_spiketest_extended(self):
dat = [-1 , 3 , 40 , -1 , 1 , -6 , -6 , 1 , 2 , 4 , 3 , 1 , -1 , 40 , 1 , 1 , 4 , 2 , 2 , 2 , 1 , 2 , 100]
out = [ 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 0 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 0]
acc = 0.1
N = 5
L = 7
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
dat = np.arange(20)
dat[0] = 100 # spike at the beginning
dat[10] = 100 # spike in the middle
dat[19] = 100 # spike at the end
out = np.empty(20, dtype=np.int8)
out.fill(1)
out[0] = 0
out[10] = 0
out[19] = 0
acc = 0.1
N = 5
L = 7 # longer smooothing
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
def test_dataqc_spiketest_random(self):
max = int(1e6)
a = np.array([10] * max)
# Set some indices to values that are within the tolerance
in_inds = np.random.randint(0,max,10)
a[in_inds] = 13
# Set some indices to values that are outside the tolerance
out_inds = np.random.randint(0,max,10)
a[out_inds] = 20
out = qcfunc.dataqc_spiketest(a, 1, N=5, L=5)
# Make sure the expected failures are 0
self.assertTrue((out[out_inds] == 0).all())
# Delete the indices and make sure everything that's left is 1
self.assertTrue((np.delete(out, out_inds) == 1).all())
def test_dataqc_spiketest_random(self):
max = int(1e6)
a = np.array([10] * max)
# Set some indices to values that are within the tolerance
in_inds = np.random.randint(0,max,10)
a[in_inds] = 13
# Set some indices to values that are outside the tolerance
out_inds = np.random.randint(0,max,10)
a[out_inds] = 20
out = qcfunc.dataqc_spiketest(a, 1, N=5, L=5)
# Make sure the expected failures are 0
self.assertTrue((out[out_inds] == 0).all())
# Delete the indices and make sure everything that's left is 1
self.assertTrue((np.delete(out, out_inds) == 1).all())
def test_dataqc_spiketest(self):
"""
Test of the Spike Test function.
Test values based on those defined in DPS:
OOI (2012). Data Product Specification for Spike Test. Document Control
Number 1341-10006. https://alfresco.oceanobservatories.org/ (See:
Company Home >> OOI >> Controlled >> 1000 System Level >>
1341-10006_Data_Product_SPEC_SPKETST_OOI.pdf)
Implemented by Christopher Wingard, April 2013
"""
dat = [-1, 3, 40, -1, 1, -6, -6, 1]
acc = 0.1
N = 5
L = 5
out = [1, 1, 0, 1, 1, 1, 1, 1]
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
def test_dataqc_spiketest(self):
"""
Test of the Spike Test function.
Test values based on those defined in DPS:
OOI (2012). Data Product Specification for Spike Test. Document Control
Number 1341-10006. https://alfresco.oceanobservatories.org/ (See:
Company Home >> OOI >> Controlled >> 1000 System Level >>
1341-10006_Data_Product_SPEC_SPKETST_OOI.pdf)
Implemented by Christopher Wingard, April 2013
"""
dat = [-1, 3, 40, -1, 1, -6, -6, 1]
acc = 0.1
N = 5
L = 5
out = [1, 1, 0, 1, 1, 1, 1, 1]
got = qcfunc.dataqc_spiketest(dat, acc, N, L)
np.testing.assert_array_equal(got,out)
