def test_get_ensemble(self):
EPSG = 32633
upper_left_x = 436100.0
upper_left_y = 7417800.0
nx = 74
ny = 94
dx = 1000.0
dy = 1000.0
# Period start
n_hours = 30
utc = api.Calendar() # No offset gives Utc
t0 = utc.time(2015, 7, 26)
period = api.UtcPeriod(t0, t0 + api.deltahours(n_hours))
t_c = t0 + api.deltahours(1)
base_dir = path.join(shyftdata_dir, "netcdf", "arome")
# pattern = "fc*.nc"
pattern = "fc_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc$"
bpoly = box(upper_left_x, upper_left_y - ny * dy,
upper_left_x + nx * dx, upper_left_y)
try:
repos = MetNetcdfDataRepository(EPSG, base_dir, filename=pattern)
data_names = ("temperature", "wind_speed", "relative_humidity")
ensemble = repos.get_forecast_ensemble(data_names,
period,
t_c,
geo_location_criteria=bpoly)
self.assertTrue(isinstance(ensemble, list))
self.assertEqual(len(ensemble), 10)
except MetNetcdfDataRepositoryError as adre:
self.skipTest(
"(test inconclusive- missing arome-data {0})".format(adre))
def test_no_point_inside_polygon_bounds(self):
EPSG, bbox, bpoly = self.arome_epsg_bbox
bounds = bpoly.bounds
bpoly = box(bounds[0], 6010000.0, bounds[2], 6035000.0)
# Period start
year = 2015
month = 8
day = 24
hour = 6
n_hours = 30
date_str = "{}{:02}{:02}_{:02}".format(year, month, day, hour)
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(year, month, day, hour)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
filename = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
reader = MetNetcdfDataRepository(EPSG,
base_dir,
filename=filename,
padding=0.0)
data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity")
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
reader.get_timeseries(data_names,
period,
geo_location_criteria=bpoly)
self.assertEqual(
"No points in dataset which are within the bounding box of the geo_location_criteria polygon.",
context.exception.args[0])
def test_utc_period_is_None(self):
EPSG, bbox, bpoly = self.arome_epsg_bbox
# Period start
utc = api.Calendar() # No offset gives Utc
t0 = utc.time(2015, 8, 24, 6)
t0_ymdhs = utc.calendar_units(t0)
date_str = "{}{:02}{:02}_{:02}".format(
*[getattr(t0_ymdhs, k) for k in ['year', 'month', 'day', 'hour']])
period = None
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
filename = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
reader = MetNetcdfDataRepository(EPSG, base_dir, filename=filename)
src_name = "temperature"
var_name_in_file = [
k for k, v in reader._arome_shyft_map.items() if v == src_name
][0]
with netCDF4.Dataset(path.join(base_dir, filename)) as ds:
var = ds.variables[var_name_in_file]
nb_timesteps = var.shape[var.dimensions.index('time')]
srcs = reader.get_timeseries((src_name, ),
period,
geo_location_criteria=bpoly)
self.assertEqual(srcs[src_name][0].ts.size(), nb_timesteps)
def test_wrong_file(self):
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(2015, 12, 25, 18)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(30))
ar1 = MetNetcdfDataRepository(32632,
shyftdata_dir,
filename="plain_wrong.nc")
ar1.get_timeseries(("temperature", ),
period,
geo_location_criteria=None)
self.assertTrue(
all(x in context.exception.args[0] for x in ["File", "not found"]))
def test_wrong_forecast(self):
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(2015, 12, 25, 18)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(30))
ar1 = MetNetcdfDataRepository(
32632,
shyftdata_dir,
filename="plain_wrong_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc")
ar1.get_forecast(("temperature", ),
period,
utc.time(t0),
geo_location_criteria=None)
self.assertTrue(
all(x in context.exception.args[0] for x in
["No matches found for file_pattern = ", "and t_c = "]))
def test_get_forecast_collection(self):
n_hours = 30
dt = api.deltahours(1)
utc = api.Calendar() # No offset gives Utc
tc = api.YMDhms(2015, 8, 24, 6)
t0 = utc.time(tc)
period = api.UtcPeriod(t0, t0 + api.deltahours(n_hours))
date_str = "{}{:02}{:02}_{:02}".format(tc.year, tc.month, tc.day,
tc.hour)
epsg, bbox, bpoly = self.arome_epsg_bbox
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
f1_elev = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
f1 = "arome_metcoop_red_default2_5km_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc$"
#f2 = "arome_metcoop_red_test2_5km_{}.nc".format(date_str)
f2 = "arome_metcoop_red_test2_5km_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc$"
ar1 = MetNetcdfDataRepository(epsg,
base_dir,
filename=f1,
allow_subset=True)
ar2 = MetNetcdfDataRepository(epsg,
base_dir,
filename=f2,
elevation_file=f1_elev,
allow_subset=True)
geo_ts_repository = GeoTsRepositoryCollection([ar1, ar2])
source_names = ("temperature", "radiation")
sources = geo_ts_repository.get_forecast(source_names,
period,
t0,
geo_location_criteria=bpoly)
self.assertTrue(all([x in source_names for x in sources]))
geo_ts_repository = GeoTsRepositoryCollection([ar1, ar2],
reduce_type="add")
with self.assertRaises(GeoTsRepositoryCollectionError) as context:
sources = geo_ts_repository.get_forecast(
("temperature", "radiation"),
period,
t0,
geo_location_criteria=bpoly)
def test_wrong_elevation_file(self):
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
MetNetcdfDataRepository(32632,
shyftdata_dir,
filename="",
elevation_file="plain_wrong.nc")
self.assertTrue(
all(x in context.exception.args[0]
for x in ["Elevation file", "not found"]))
def __init__(self,
epsg,
filename,
padding=15000.,
flattened=False,
allow_year_shift=True,
cache_data=True):
"""
Construct the netCDF4 dataset reader for concatenated gridded forecasts and initialize data retrieval.
Parameters
----------
epsg: string
Unique coordinate system id for result coordinates. Currently "32632" and "32633" are supported.
filename: string
Path to netcdf file containing concatenated forecasts
flattened: bool
Flags whether grid_points are flattened
allow_year_shift: bool
Flags whether shift of years is allowed
"""
self.allow_year_shift = allow_year_shift
self.cache_data = cache_data
self.cache = None
if flattened:
self.wx_repo = ConcatDataRepository(epsg,
filename,
padding=padding)
elif not flattened:
self.wx_repo = MetNetcdfDataRepository(epsg,
None,
filename,
padding=padding)
filename = os.path.expandvars(filename)
with Dataset(filename) as dataset:
time = dataset.variables.get("time", None)
time = convert_netcdf_time(time.units, time)
self.wx_repo.time = time
self.source_type_map = {
"relative_humidity": api.RelHumSource,
"temperature": api.TemperatureSource,
"precipitation": api.PrecipitationSource,
"radiation": api.RadiationSource,
"wind_speed": api.WindSpeedSource
}
self.source_vector_map = {
"relative_humidity": api.RelHumSourceVector,
"temperature": api.TemperatureSourceVector,
"precipitation": api.PrecipitationSourceVector,
"radiation": api.RadiationSourceVector,
"wind_speed": api.WindSpeedSourceVector
}
def test_get_ensemble_forecast_collection(self):
EPSG = 32633
upper_left_x = 436100.0
upper_left_y = 7417800.0
nx = 74
ny = 94
dx = 1000.0
dy = 1000.0
t0 = api.YMDhms(2015, 7, 26, 0)
n_hours = 30
utc = api.Calendar() # No offset gives Utc
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
t_c = utc.time(t0) + api.deltahours(1)
base_dir = path.join(shyftdata_dir, "netcdf", "arome")
# pattern = "fc*.nc"
pattern = "fc_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc$"
bpoly = box(upper_left_x, upper_left_y - ny * dy,
upper_left_x + nx * dx, upper_left_y)
try:
ar1 = MetNetcdfDataRepository(EPSG, base_dir, filename=pattern)
ar2 = MetNetcdfDataRepository(EPSG, base_dir, filename=pattern)
repos = GeoTsRepositoryCollection([ar1, ar2])
data_names = ("temperature", "wind_speed", "relative_humidity")
ensemble = repos.get_forecast_ensemble(data_names, period, t_c,
None)
self.assertTrue(isinstance(ensemble, list))
self.assertEqual(len(ensemble), 10)
with self.assertRaises(GeoTsRepositoryCollectionError) as context:
repos = GeoTsRepositoryCollection([ar1, ar2],
reduce_type="add")
repos.get_forecast_ensemble(data_names,
period,
t_c,
geo_location_criteria=bpoly)
self.assertEqual("Only replace is supported yet",
context.exception.args[0])
except MetNetcdfDataRepositoryError as adre:
self.skipTest(
"(test inconclusive- missing arome-data {0})".format(adre))
def test_get_timeseries_collection(self):
tc = api.YMDhms(2015, 8, 24, 6)
n_hours = 30
dt = api.deltahours(1)
utc = api.Calendar() # No offset gives Utc
t0 = utc.time(tc)
period = api.UtcPeriod(t0, t0 + api.deltahours(n_hours))
date_str = "{}{:02}{:02}_{:02}".format(tc.year, tc.month, tc.day,
tc.hour)
epsg, bbox, bpoly = self.arome_epsg_bbox
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
f1 = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
f2 = "arome_metcoop_red_test2_5km_{}.nc".format(date_str)
ar1 = MetNetcdfDataRepository(epsg,
base_dir,
filename=f1,
allow_subset=True)
ar2 = MetNetcdfDataRepository(epsg,
base_dir,
filename=f2,
elevation_file=f1,
allow_subset=True)
geo_ts_repository = GeoTsRepositoryCollection([ar1, ar1, ar2])
sources_replace = geo_ts_repository.get_timeseries(
("temperature", "radiation"), period, geo_location_criteria=bpoly)
with self.assertRaises(GeoTsRepositoryCollectionError) as context:
GeoTsRepositoryCollection([ar1, ar2], reduce_type="foo")
geo_ts_repository = GeoTsRepositoryCollection([ar1, ar1, ar2],
reduce_type="add")
sources_add = geo_ts_repository.get_timeseries(
("temperature", "radiation"), period, geo_location_criteria=bpoly)
self.assertGreater(len(sources_add["temperature"]),
len(sources_replace["temperature"]))
def test_get_forecast(self):
# Period start
n_hours = 65
utc = api.Calendar() # No offset gives Utc
t0 = utc.time(2015, 8, 24, 6)
period1 = api.UtcPeriod(t0, t0 + api.deltahours(n_hours))
period2 = api.UtcPeriod(
t0 + api.deltahours(6),
t0 + api.deltahours(6) + api.deltahours(n_hours))
t_c1 = t0 + api.deltahours(1)
t_c2 = t0 + api.deltahours(7)
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
# pattern = "arome_metcoop*default2_5km_*.nc"
pattern = "arome_metcoop_red_default2_5km_(\d{4})(\d{2})(\d{2})[T_](\d{2})Z?.nc$"
EPSG, bbox, bpoly = self.arome_epsg_bbox
repos = MetNetcdfDataRepository(EPSG, base_dir, filename=pattern)
data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity")
tc1_sources = repos.get_forecast(data_names,
period1,
t_c1,
geo_location_criteria=bpoly)
tc2_sources = repos.get_forecast(data_names,
period2,
t_c2,
geo_location_criteria=bpoly)
self.assertTrue(len(tc1_sources) == len(tc2_sources))
self.assertTrue(set(tc1_sources) == set(data_names))
self.assertTrue(tc1_sources["temperature"][0].ts.size() == n_hours + 1)
tc1_precip = tc1_sources["precipitation"][0].ts
tc2_precip = tc2_sources["precipitation"][0].ts
self.assertEqual(tc1_precip.size(), n_hours)
self.assertTrue(tc1_precip.time(0) != tc2_precip.time(0))
def test_tiny_bbox(self):
EPSG, _, _ = self.arome_epsg_bbox
x = 432425.910493 # x coord of one pt in test file
y = 6819847.92879 # y coord of one pt in test file
dxy = 1000. # should be less than the grid resolution (2500 m) to enclose only one point
bpoly = box(x - dxy, y - dxy, x + dxy,
y + dxy) # a polygon containing only tht above point
# Period start
year = 2015
month = 8
day = 24
hour = 6
n_hours = 30
date_str = "{}{:02}{:02}_{:02}".format(year, month, day, hour)
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(year, month, day, hour)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
filename = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
reader = MetNetcdfDataRepository(EPSG,
base_dir,
filename=filename,
padding=0.0)
data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity")
try:
tss = reader.get_timeseries(data_names,
period,
geo_location_criteria=bpoly)
except MetNetcdfDataRepositoryError as err:
self.fail(
"reader.get_timeseries raised MetNetcdfDataRepositoryError('{}') "
"unexpectedly.".format(err.args[0]))
self.assertEqual(len(tss['temperature']), 1)
def test_geo_location_criteria_is_None(self):
EPSG, _, _ = self.arome_epsg_bbox
# Period start
year = 2015
month = 8
day = 24
hour = 6
n_hours = 30
date_str = "{}{:02}{:02}_{:02}".format(year, month, day, hour)
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(year, month, day, hour)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
filename = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
reader = MetNetcdfDataRepository(EPSG, base_dir, filename=filename)
data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity")
with netCDF4.Dataset(path.join(base_dir, filename)) as ds:
nb_pts_in_file = ds.dimensions['x'].size * ds.dimensions['y'].size
srcs = reader.get_timeseries(data_names, period, None)
self.assertEqual(len(srcs['temperature']), nb_pts_in_file)
def test_get_timeseries(self):
"""
Simple regression test of arome data respository.
"""
EPSG, bbox, bpoly = self.arome_epsg_bbox
# Period start
n_hours = 30
t0 = api.YMDhms(2015, 8, 24, 0)
date_str = "{}{:02}{:02}_{:02}".format(t0.year, t0.month, t0.day,
t0.hour)
utc = api.Calendar() # No offset gives Utc
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
f1 = "arome_metcoop_red_default2_5km_{}_diff_time_unit.nc".format(
date_str)
f2 = "arome_metcoop_red_test2_5km_{}.nc".format(date_str)
ar1 = MetNetcdfDataRepository(EPSG, base_dir, filename=f1)
ar2 = MetNetcdfDataRepository(EPSG,
base_dir,
filename=f2,
elevation_file=f1)
ar1_data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity")
ar2_data_names = ("radiation", )
sources = ar1.get_timeseries(ar1_data_names,
period,
geo_location_criteria=bpoly)
self.assertTrue(len(sources) > 0)
sources2 = ar2.get_timeseries(ar2_data_names,
period,
geo_location_criteria=bpoly)
self.assertTrue(set(sources) == set(ar1_data_names))
self.assertTrue(set(sources2) == set(ar2_data_names))
self.assertTrue(sources["temperature"][0].ts.size() == n_hours + 1)
r0 = sources2["radiation"][0].ts
p0 = sources["precipitation"][0].ts
temp0 = sources["temperature"][0].ts
self.assertTrue(r0.size() == n_hours)
self.assertTrue(p0.size() == n_hours)
self.assertTrue(r0.time(0) == temp0.time(0))
self.assertTrue(p0.time(0) == temp0.time(0))
self.assertTrue(
r0.time_axis.total_period().end == temp0.time(temp0.size() - 1))
self.assertTrue(
p0.time_axis.total_period().end == temp0.time(temp0.size() - 1))
self.assertTrue(p0.time(0), period.start)
def test_run_arome_ensemble(self):
# Simulation time axis
utc = api.Calendar() # No offset gives Utc
t0 = utc.time(2015, 7, 26, 0)
n_hours = 30
dt = api.deltahours(1)
time_axis = api.TimeAxisFixedDeltaT(t0, dt, n_hours)
# Some dummy ids not needed for the netcdf based repositories
region_id = 0
interpolation_id = 0
# Simulation coordinate system
epsg = "32633"
# Configs and repositories
region_model_repository = CFRegionModelRepository(
self.region_config, self.model_config)
interp_repos = InterpolationParameterRepository(
self.interpolation_config)
base_dir = path.join(shyftdata_dir, "netcdf", "arome")
pattern = "fc*.nc"
try:
geo_ts_repository = MetNetcdfDataRepository(epsg,
base_dir,
filename=pattern,
allow_subset=True)
except Exception as e:
print("**** test_run_arome_ensemble: Arome data missing or"
" wrong, test inconclusive ****")
print("****{}****".format(e))
self.skipTest(
"**** test_run_arome_ensemble: Arome data missing or wrong, test "
"inconclusive ****\n\t exception:{}".format(e))
simulator = DefaultSimulator(region_id, interpolation_id,
region_model_repository,
geo_ts_repository, interp_repos, None)
state_repos = DefaultStateRepository(simulator.region_model)
simulators = simulator.create_ensembles(time_axis, t0,
state_repos.get_state(0))
for s in simulators:
s.simulate()
def test_subsets(self):
EPSG, bbox, bpoly = self.arome_epsg_bbox
# Period start
year = 2015
month = 8
day = 24
hour = 6
n_hours = 30
date_str = "{}{:02}{:02}_{:02}".format(year, month, day, hour)
utc = api.Calendar() # No offset gives Utc
t0 = api.YMDhms(year, month, day, hour)
period = api.UtcPeriod(utc.time(t0),
utc.time(t0) + api.deltahours(n_hours))
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
filename = "arome_metcoop_red_default2_5km_{}.nc".format(date_str)
data_names = ("temperature", "wind_speed", "precipitation",
"relative_humidity", "radiation")
allow_subset = False
reader = MetNetcdfDataRepository(EPSG,
base_dir,
filename=filename,
allow_subset=allow_subset)
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
reader.get_timeseries(data_names, period, None)
self.assertEqual("Could not find all data fields",
context.exception.args[0])
allow_subset = True
reader = MetNetcdfDataRepository(EPSG,
base_dir,
filename=filename,
allow_subset=allow_subset)
try:
sources = reader.get_timeseries(data_names,
period,
geo_location_criteria=bpoly)
except MetNetcdfDataRepositoryError as e:
self.fail(
"MetNetcdfDataRepository.get_timeseries(data_names, period, None) "
"raised MetNetcdfDataRepositoryError unexpectedly.")
self.assertEqual(len(sources), len(data_names) - 1)
def test_transform_functions_variable_interval(self):
"""
test the _transform_raw function.
"""
EPSG, bbox, bpoly = self.arome_epsg_bbox
# Period start
n_hours = 30
t0 = api.YMDhms(2015, 8, 24, 0)
date_str = "{}{:02}{:02}_{:02}".format(t0.year, t0.month, t0.day,
t0.hour)
utc = api.Calendar() # No offset gives Utc
base_dir = path.join(shyftdata_dir, "repository",
"arome_data_repository")
f1 = "arome_metcoop_red_default2_5km_{}_diff_time_unit.nc".format(
date_str)
ar1 = MetNetcdfDataRepository(EPSG, base_dir, filename=f1)
np_raw_array = np.array(
[ # 0 # 1 # 2 # 3
[1.0, 2.0, 3.0, 4.0], [1.1, 2.1, 3.1, 4.1],
[1.2, 2.2, 3.2, 4.2], [1.4, 2.5, 3.6, 4.7]
],
dtype=np.float64)
raw_values = {
'wind_speed': (np_raw_array, 'wind_speed', 'm/s'),
'rel_hum': (np_raw_array, 'relative_humidity_2m', '?'),
'temperature': (273.15 + np_raw_array, 'air_temperature_2m', 'K'),
'radiation':
(3600.0 * np_raw_array,
'integral_of_surface_downwelling_shortwave_flux_in_air_wrt_time',
'W s/m2'),
'prepitation_acc':
(np_raw_array, 'precipitation_amount_acc', 'Mg/m^2'),
'prepitation': (np_raw_array, 'precipitation_amount', 'mm')
}
raw_time = np.array([0, 3600, 7200, 7200 + 2 * 3600],
dtype=np.int64) # last step is 2 hours!
rd = ar1._transform_raw(raw_values, raw_time)
ta3 = api.TimeAxis(api.UtcTimeVector(raw_time[:-1]),
api.time(int(raw_time[-1])))
ta4 = api.TimeAxis(
api.UtcTimeVector(raw_time),
api.time(int(raw_time[-1] +
2 * 3600))) # assume last step is also 2 hours
e_precip_acc = np.array(
[ # 0 # 1 # 2 # 3
[100.0, 100.0, 100.0, 100.0],
[100.0, 100.0, 100.0, 100.0],
[100.0, 150.0, 200.0, 250.0],
],
dtype=np.float64)
e_precip = np.array(
[ # 0 # 1 # 2 # 3
[1.1, 2.1, 3.1, 4.1], [1.2, 2.2, 3.2, 4.2],
[1.4, 2.5, 3.6, 4.7]
],
dtype=np.float64)
e_rad = np.array(
[ # 0 # 1 # 2 # 3
[0.1, 0.1, 0.1, 0.1],
[0.1, 0.1, 0.1, 0.1],
[0.1, 0.15, 0.2, 0.25],
],
dtype=np.float64)
e = {
'wind_speed': (np_raw_array, ta4),
'rel_hum': (np_raw_array, ta4),
'temperature': (np_raw_array, ta4),
'radiation': (e_rad, ta3),
'prepitation_acc': (e_precip_acc, ta3),
'prepitation': (e_precip, ta3)
}
self.assertIsNotNone(rd)
for k, r in rd.items():
self.assertTrue(k in e)
self.assertEqual(r[1], e[k][1], "expect correct time-axis")
self.assertTrue(np.allclose(r[0], e[k][0]),
"expect exact correct values")
def test_wrong_directory(self):
with self.assertRaises(MetNetcdfDataRepositoryError) as context:
MetNetcdfDataRepository(32632, "Foobar", filename="")
self.assertEqual("No such directory 'Foobar'",
context.exception.args[0])