def test_unwrap_ts_many_splits(self):
"""
Nominal test using a timeseries composed of many discontinuities (5000)
Check the successive discontinuities doesn't alter the result
"""
# Create test timeseries : (splits+1) * num items
fid = "UT_Unwrap_many_splits"
discontinuity = 180
pattern_to_use = np.linspace(-180, 180, 5)
splits = 5000
# Generated TS has (5000+1)*5 points
tsuid, generated_nb_points = generate_ts(fid=fid,
splits=splits,
pattern=pattern_to_use)
# Create expected result
expected_points = calc_expected_ts(splits=splits,
pattern=pattern_to_use,
phase=discontinuity,
period=1000)
fid_pattern = "%(fid)s__unwrap"
try:
# Call algorithm
results, timings = unwrap_tsuid(tsuid=tsuid,
unit=TSUnit.Degrees,
discontinuity=discontinuity,
fid_pattern=fid_pattern)
# Get results
obtained_points = IkatsApi.ts.read(
tsuid_list=[results["tsuid"]])[0]
# Check results
self.assertEqual(generated_nb_points, len(obtained_points))
self.assertTrue(
np.allclose(expected_points.astype(float),
obtained_points.astype(float)))
LOGGER.info('Stats :%s', timings.stats())
except AssertionError:
raise
finally:
# Clear Data
# Delete the TS
IkatsApi.ts.delete(tsuid=tsuid, no_exception=True)
# Delete the result TS
IkatsApi.ts.delete(tsuid=IkatsApi.fid.tsuid(fid=fid_pattern %
({
'fid': fid
})),
no_exception=True)
def test_unwrap_ts_many_chunks(self):
"""
Nominal test forcing several chunks
Check the chunks of TS are combined properly into the final TS
"""
# Create test timeseries
fid = "UT_Unwrap_many_chunks"
discontinuity = 180
pattern_to_use = np.array([-180, -90, 0, 90, 180])
splits = 3
# Generated TS has (2+1)*5 points
tsuid, generated_nb_points = generate_ts(fid=fid,
splits=splits,
pattern=pattern_to_use)
# Create expected result
expected_points = calc_expected_ts(splits=splits,
pattern=pattern_to_use,
phase=discontinuity)
fid_pattern = "%(fid)s__unwrap"
try:
# Call algorithm
# Force a small chunk_size to have several chunks (chunk_size=3, instead of 75000 by default)
results, _ = unwrap_tsuid(tsuid=tsuid,
unit=TSUnit.Degrees,
discontinuity=discontinuity,
fid_pattern=fid_pattern,
chunk_size=3)
# Get results
obtained_points = IkatsApi.ts.read(
tsuid_list=[results["tsuid"]])[0]
# Check results
self.assertEqual(generated_nb_points, len(obtained_points))
self.assertTrue(
np.allclose(expected_points.astype(float),
obtained_points.astype(float)))
except AssertionError:
raise
finally:
# Clear Data
# Delete the TS
IkatsApi.ts.delete(tsuid=tsuid, no_exception=True)
# Delete the result TS
IkatsApi.ts.delete(tsuid=IkatsApi.fid.tsuid(fid=fid_pattern %
({
'fid': fid
})),
no_exception=True)
def test_unwrap_tsuid_degrees(self):
"""
Nominal test using degrees values
Check the degrees series are well handled
"""
# Create test timeseries
fid = "UT_Unwrap_degrees"
discontinuity = 180
pattern_to_use = np.array([-180, -90, 0, 90, 180])
splits = 2
# Generated TS has (2+1)*5 points
tsuid, generated_nb_points = generate_ts(fid=fid,
splits=splits,
pattern=pattern_to_use)
# Create expected result
expected_points = calc_expected_ts(splits=splits,
pattern=pattern_to_use,
phase=discontinuity)
fid_pattern = "%(fid)s__unwrap"
try:
# Call algorithm
results, _ = unwrap_tsuid(tsuid=tsuid,
unit=TSUnit.Degrees,
discontinuity=discontinuity,
fid_pattern=fid_pattern)
# Get results
obtained_points = IkatsApi.ts.read(
tsuid_list=[results["tsuid"]])[0]
# Check results
self.assertEqual(generated_nb_points, len(obtained_points))
self.assertTrue(
np.allclose(expected_points.astype(float),
obtained_points.astype(float)))
except AssertionError:
raise
finally:
# Clear Data
# Delete the TS
IkatsApi.ts.delete(tsuid=tsuid, no_exception=True)
# Delete the result TS
IkatsApi.ts.delete(tsuid=IkatsApi.fid.tsuid(fid=fid_pattern %
({
'fid': fid
})),
no_exception=True)
def test_unwrap_ts_single_point(self):
"""
Nominal test using radian values with only one point
Check a TS having 1 point doesn't produce error
"""
# Create test timeseries
fid = "UT_Unwrap_single"
discontinuity = pi
pattern_to_use = np.array([42])
splits = 0
# Generated TS has 1 point
tsuid, generated_nb_points = generate_ts(fid=fid,
splits=splits,
pattern=pattern_to_use)
# Create expected result
expected_points = calc_expected_ts(splits=splits,
pattern=pattern_to_use,
phase=discontinuity,
period=1000)
fid_pattern = "%(fid)s__unwrap"
try:
# Call algorithm
results, _ = unwrap_tsuid(tsuid=tsuid,
unit=TSUnit.Radians,
discontinuity=discontinuity,
fid_pattern=fid_pattern)
# Get results
obtained_points = IkatsApi.ts.read(
tsuid_list=[results["tsuid"]])[0]
# Check results
self.assertEqual(generated_nb_points, len(obtained_points))
self.assertTrue(
np.allclose(expected_points.astype(float),
obtained_points.astype(float)))
except AssertionError:
raise
finally:
# Clear Data
# Delete the TS
IkatsApi.ts.delete(tsuid=tsuid, no_exception=True)
# Delete the result TS
IkatsApi.ts.delete(tsuid=IkatsApi.fid.tsuid(fid=fid_pattern %
({
'fid': fid
})),
no_exception=True)