def test_flip_depths(self):
ncfile1 = os.path.join(os.path.dirname(__file__), 'resources', 'sensor_with_depths_3.nc')
ncd1 = EnhancedDataset(ncfile1)
ncvar1 = ncd1.variables['soil_moisture_percent']
df1 = get_dataframe_from_variable(ncd1, ncvar1)
assert np.allclose(df1.depth.unique(), np.asarray([-0.0508, -0.2032, -0.508]))
def test_sensor_with_depths(self):
ncfile1 = os.path.join(os.path.dirname(__file__), 'resources', 'sensor_with_depths_1.nc')
ncd1 = EnhancedDataset(ncfile1)
ncvar1 = ncd1.variables['soil_moisture_percent']
df1 = get_dataframe_from_variable(ncd1, ncvar1)
ncd1.close()
ncfile2 = os.path.join(os.path.dirname(__file__), 'resources', 'sensor_with_depths_2.nc')
ncd2 = EnhancedDataset(ncfile2)
ncvar2 = ncd2.variables['soil_moisture_percent']
df2 = get_dataframe_from_variable(ncd2, ncvar2)
ncd2.close()
df = df2.combine_first(df1)
assert not df.empty
def test_sensor_with_depths(self):
ncfile1 = os.path.join(os.path.dirname(__file__), 'resources', 'sensor_with_depths_1.nc')
ncd1 = EnhancedDataset(ncfile1)
ncvar1 = ncd1.variables['soil_moisture_percent']
df1 = get_dataframe_from_variable(ncd1, ncvar1)
ncd1.close()
ncfile2 = os.path.join(os.path.dirname(__file__), 'resources', 'sensor_with_depths_2.nc')
ncd2 = EnhancedDataset(ncfile2)
ncvar2 = ncd2.variables['soil_moisture_percent']
df2 = get_dataframe_from_variable(ncd2, ncvar2)
ncd2.close()
df = df2.combine_first(df1)
assert not df.empty
def test_extracting_dataframe_some_masked_heights(self):
filename = 'test_extracting_dataframe_some_masked_heights.nc'
times = [0, 1000, 2000, 3000, 4000, 5000]
verticals = [-9999.9, 7.8, 7.9]
ts = TimeSeries(output_directory=self.output_directory,
latitude=self.latitude,
longitude=self.longitude,
station_name=self.station_name,
global_attributes=self.global_attributes,
output_filename=filename,
times=times,
verticals=verticals,
vertical_fill=-9999.9)
values = np.repeat([20, 21, 22, 23, 24, 25], len(verticals))
attrs = dict(standard_name='sea_water_temperature')
ts.add_variable('temperature', values=values, attributes=attrs)
nc = netCDF4.Dataset(os.path.join(self.output_directory, filename))
assert nc is not None
assert nc.variables.get('time').size == len(times)
assert nc.variables.get('time')[:].dtype == np.int32
assert nc.variables.get('z').size == len(verticals)
assert nc.variables.get('z')[:].dtype == np.float64
assert np.allclose(nc.variables.get('z')[:], np.ma.array([np.nan, 7.8, 7.9], mask=[1, 0, 0]))
assert nc.variables.get('temperature').size == len(times) * len(verticals)
df = get_dataframe_from_variable(nc, nc.variables.get('temperature'))
assert not df['depth'].dropna().empty
def test_extracting_dataframe_ordered_masked_heights(self):
filename = 'test_extracting_dataframe_ordered_masked_heights.nc'
times = [0, 1000, 2000, 3000, 4000, 5000]
verticals = [np.nan, 7.8]
ts = TimeSeries(output_directory=self.output_directory,
latitude=self.latitude,
longitude=self.longitude,
station_name=self.station_name,
global_attributes=self.global_attributes,
output_filename=filename,
times=times,
verticals=verticals,
vertical_fill=np.nan)
values = np.asarray([[20, 21], [22, 23], [24, 25], [30, 31], [32, 33],
[34, 35]])
attrs = dict(standard_name='sea_water_temperature')
ts.add_variable('temperature', values=values, attributes=attrs)
nc = netCDF4.Dataset(os.path.join(self.output_directory, filename))
assert nc is not None
assert nc.variables.get('time').size == len(times)
assert nc.variables.get('time')[:].dtype == np.int32
assert nc.variables.get('z').size == len(verticals)
assert nc.variables.get('z')[:].dtype == np.float64
# The height order is sorted!
assert np.allclose(
nc.variables.get('z')[:], np.ma.array([7.8, np.nan], mask=[0, 1]))
assert nc.variables.get(
'temperature').size == len(times) * len(verticals)
# Be sure the values are re-arranged because the height order is sorted!
assert np.isclose(nc.variables.get('temperature')[:][0][0], 21)
assert np.isclose(nc.variables.get('temperature')[:][1][0], 23)
assert np.isclose(nc.variables.get('temperature')[:][2][0], 25)
assert np.isclose(nc.variables.get('temperature')[:][3][0], 31)
assert np.isclose(nc.variables.get('temperature')[:][4][0], 33)
assert np.isclose(nc.variables.get('temperature')[:][5][0], 35)
df = get_dataframe_from_variable(nc, nc.variables.get('temperature'))
assert not df['depth'].dropna().empty