def test_dataqc_localrangetest_data(self):
testcases = [
'test-data/dataqc_localrangetest_testcase01.mat',
'test-data/dataqc_localrangetest_testcase02.mat',
# This one fails because MATLAB has a different interpolation alg
#'test-data/dataqc_localrangetest_testcase03.mat',
]
for tc in testcases:
if not os.path.exists(tc):
raise unittest.SkipTest('%s not found' % tc)
import scipy.io
mat = scipy.io.loadmat(tc)
dat = mat['dat']
dat = dat[:,0]
z = mat['z']
z = z[:,0]
datlimz = mat['datlimz']
datlimz = datlimz[:,0]
datlim = mat['datlim']
expected = mat['out']
expected = expected[:,0]
qc = qcfunc.dataqc_localrangetest(dat, z, datlim, datlimz)
np.testing.assert_array_equal(qc, expected)
def test_dataqc_localrangetest(self):
"""
Test of the dataqc_localrangetest function.
Test values calculated in Matlab R2012b using DPS function.
OOI (2012). Data Product Specification for Local Range Test. Document
Control Number 1341-10005. https://alfresco.oceanobservatories.org/
(See: Company Home >> OOI >> Controlled >> 1000 System Level >>
1341-10005_Data_Product_SPEC_LOCLRNG_OOI.pdf)
Implemented by Christopher Wingard, April 2013
"""
dat = np.array([3.5166, 8.3083, 5.8526, 5.4972, 9.1719,
2.8584, 7.5720, 7.5373, 3.8045, 5.6782])
z = np.array([0.1517, 0.1079, 1.0616, 1.5583, 1.8680,
0.2598, 1.1376, 0.9388, 0.0238, 0.6742])
datlim = np.array([[0, 2], [0, 2], [1, 8], [1, 9], [1, 10]])
datlimz = np.array([0, 0.5, 1, 1.5, 2])
qcflag = np.array([0, 0, 1, 1, 1, 0, 1, 0, 0, 0], dtype='int8')
got = qcfunc.dataqc_localrangetest(dat, z, datlim, datlimz)
self.assertTrue(np.array_equal(got, qcflag))
def test_dataqc_localrangetest_data(self):
testcases = [
'test-data/dataqc_localrangetest_testcase01.mat',
'test-data/dataqc_localrangetest_testcase02.mat',
# This one fails because MATLAB has a different interpolation alg
#'test-data/dataqc_localrangetest_testcase03.mat',
]
for tc in testcases:
if not os.path.exists(tc):
raise unittest.SkipTest('%s not found' % tc)
import scipy.io
mat = scipy.io.loadmat(tc)
dat = mat['dat']
dat = dat[:,0]
z = mat['z']
z = z[:,0]
datlimz = mat['datlimz']
datlimz = datlimz[:,0]
datlim = mat['datlim']
expected = mat['out']
expected = expected[:,0]
qc = qcfunc.dataqc_localrangetest(dat, z, datlim, datlimz)
np.testing.assert_array_equal(qc, expected)
def test_dataqc_localrangetest(self):
"""
Test of the dataqc_localrangetest function.
Test values calculated in Matlab R2012b using DPS function.
OOI (2012). Data Product Specification for Local Range Test. Document
Control Number 1341-10005. https://alfresco.oceanobservatories.org/
(See: Company Home >> OOI >> Controlled >> 1000 System Level >>
1341-10005_Data_Product_SPEC_LOCLRNG_OOI.pdf)
Implemented by Christopher Wingard, April 2013
"""
dat = np.array([3.5166, 8.3083, 5.8526, 5.4972, 9.1719,
2.8584, 7.5720, 7.5373, 3.8045, 5.6782])
z = np.array([0.1517, 0.1079, 1.0616, 1.5583, 1.8680,
0.2598, 1.1376, 0.9388, 0.0238, 0.6742])
datlim = np.array([[0, 2], [0, 2], [1, 8], [1, 9], [1, 10]])
datlimz = np.array([0, 0.5, 1, 1.5, 2])
qcflag = np.array([0, 0, 1, 1, 1, 0, 1, 0, 0, 0], dtype='int8')
got = qcfunc.dataqc_localrangetest(dat, z, datlim, datlimz)
self.assertTrue(np.array_equal(got, qcflag))
def process_local_range_test(self, coverage, parameter, input_name, datlim, datlimz):
qc_array = coverage.get_parameter_values(parameter.name)
indexes = np.where(qc_array == -88)[0]
from ion_functions.qc.qc_functions import dataqc_localrangetest
value_array = coverage.get_parameter_values(input_name)
# z_parameter_name needs to come from, I guess the column headings...
# I also need to deal with the case where there are multiple axes...
# I don't have a good feeling about this.
z_parameter_name = None
z_array = coverage.get_parameter_values(z_parameter_name)
qc_array = dataqc_localrangetest(value_array, z_array, datlim, datlimz)
return_dictionary = {
coverage.temporal_parameter_name : time_array[indexes],
parameter.name : qc_array[indexes]
}
