def _convert_to_reltime(time):
"""Check to determine if the value of the time parameter needs to be
converted to a relative value (relative to the time_origin).
"""
if isinstance(time, np.datetime64) or (hasattr(
time, 'calendar') and time.calendar in _get_cftime_calendars()):
return True
return False
@pytest.mark.parametrize('ydim', [100, 200])
def test_fieldset_from_parcels(xdim, ydim, tmpdir, filename='test_parcels'):
""" Simple test for fieldset initialisation from Parcels FieldSet file format. """
filepath = tmpdir.join(filename)
data, dimensions = generate_fieldset(xdim, ydim)
fieldset_out = FieldSet.from_data(data, dimensions)
fieldset_out.write(filepath)
fieldset = FieldSet.from_parcels(filepath)
assert len(fieldset.U.data.shape) == 3 # Will be 4 once we use depth
assert len(fieldset.V.data.shape) == 3
assert np.allclose(fieldset.U.data[0, :], data['U'], rtol=1e-12)
assert np.allclose(fieldset.V.data[0, :], data['V'], rtol=1e-12)
@pytest.mark.parametrize('calendar, cftime_datetime',
zip(_get_cftime_calendars(),
_get_cftime_datetimes()))
def test_fieldset_nonstandardtime(calendar, cftime_datetime, tmpdir, filename='test_nonstandardtime.nc', xdim=4, ydim=6):
filepath = tmpdir.join(filename)
dates = [getattr(cftime, cftime_datetime)(1, m, 1) for m in range(1, 13)]
da = xr.DataArray(np.random.rand(12, xdim, ydim),
coords=[dates, range(xdim), range(ydim)],
dims=['time', 'lon', 'lat'], name='U')
da.to_netcdf(str(filepath))
dims = {'lon': 'lon', 'lat': 'lat', 'time': 'time'}
try:
field = Field.from_netcdf(filepath, 'U', dims)
except NotImplementedError:
field = None
def _convert_to_reltime(time):
if isinstance(time, np.datetime64) or (hasattr(time, 'calendar')
and time.calendar
in _get_cftime_calendars()):
return True
return False
def test_set_calendar():
for calendar_name, cf_datetime in zip(_get_cftime_calendars(),
_get_cftime_datetimes()):
date = getattr(cftime, cf_datetime)(1990, 1, 1)
assert _set_calendar(date.calendar) == date.calendar
assert _set_calendar('np_datetime64') == 'standard'
@pytest.mark.parametrize('ydim', [100, 200])
def test_fieldset_from_parcels(xdim, ydim, tmpdir, filename='test_parcels'):
""" Simple test for fieldset initialisation from Parcels FieldSet file format. """
filepath = tmpdir.join(filename)
data, dimensions = generate_fieldset(xdim, ydim)
fieldset_out = FieldSet.from_data(data, dimensions)
fieldset_out.write(filepath)
fieldset = FieldSet.from_parcels(filepath)
assert len(fieldset.U.data.shape) == 3 # Will be 4 once we use depth
assert len(fieldset.V.data.shape) == 3
assert np.allclose(fieldset.U.data[0, :], data['U'], rtol=1e-12)
assert np.allclose(fieldset.V.data[0, :], data['V'], rtol=1e-12)
@pytest.mark.parametrize('calendar, cftime_datetime',
zip(_get_cftime_calendars(), _get_cftime_datetimes()))
def test_fieldset_nonstandardtime(calendar,
cftime_datetime,
tmpdir,
filename='test_nonstandardtime.nc',
xdim=4,
ydim=6):
filepath = tmpdir.join(filename)
dates = [getattr(cftime, cftime_datetime)(1, m, 1) for m in range(1, 13)]
da = xr.DataArray(np.random.rand(12, xdim, ydim),
coords=[dates, range(xdim),
range(ydim)],
dims=['time', 'lon', 'lat'],
name='U')
da.to_netcdf(str(filepath))
