def test_wind_mover():
'''
Use a wind_mover, about as simple as it comes
- We are moving to a design where the environment objects contain the
extrapolate flag instead of the movers. This flag is off by default.
'''
# fake data arrays:
num = 2
pos_dt = np.dtype([('lon', np.float),
('lat', np.float),
('depth', np.float)])
sc = SC({'positions': np.zeros((num,), dtype=pos_dt),
'status_codes': np.zeros((num,), dtype=np.int16),
'windages': np.zeros((num,)),
})
wind = wind_from_values([(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
])
wm = WindMover(wind)
# within the model's time span, this should work:
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 12, 20))
# before time span -- this should fail
with pytest.raises(RuntimeError):
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
# after time span -- this should fail
with pytest.raises(RuntimeError):
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 12, 50))
# turn on extrapolation in the wind environment object
wind.extrapolation_is_allowed = True
# before timespan -- this should pass now
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
# after timespan -- this should pass now
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 12, 50))
# test the error message that we get when a RuntimeError is raised.
with pytest.raises(RuntimeError):
try:
wind.extrapolation_is_allowed = False
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
except RuntimeError as err:
msg = err.args[0]
assert "No available data" in msg
assert "WindMover" in msg
assert "2016-05-10 11:50:00" in msg
assert "2016-05-10 12:00:00" in msg
assert "2016-05-10 12:40:00" in msg
raise
def test_wind_from_values():
"""
simple test for the utility
"""
values = [(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
]
wind = wind_from_values(values)
# see if it's got the correct data
for dt, r, theta in values:
vals = wind.get_value(dt)
assert np.allclose(vals[0], r)
assert np.allclose(vals[1], theta)
def test_wind_from_values_knots():
"""
simple test for the utility == passing in knots
"""
values = [(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
]
wind = wind_from_values(values, units='knot')
# see if it's got the correct data
for dt, r, theta in values:
vals = wind.get_value(dt)
assert np.allclose(vals[0], unit_conversion.convert('velocity', 'knot', 'm/s', r))
assert np.allclose(vals[1], theta)
def test_wind_from_values():
"""
simple test for the utility
"""
values = [(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
]
wind = wind_from_values(values)
# see if it's got the correct data
for dt, r, theta in values:
vals = wind.get_value(dt)
assert np.allclose(vals[0], r)
assert np.allclose(vals[1],theta)
def test_wind_from_values_knots():
"""
simple test for the utility == passing in knots
"""
values = [(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
]
wind = wind_from_values(values, units='knot')
# see if it's got the correct data
for dt, r, theta in values:
vals = wind.get_value(dt)
assert np.allclose(vals[0], unit_conversion.convert('velocity',
'knot', 'm/s', r))
assert np.allclose(vals[1], theta)
def test_wind_mover():
"""
use a wind_mover, about as simple as it comes
"""
# fake data arrays:
num = 2
pos_dt = np.dtype([('lon', np.float), ('lat', np.float), ('depth', np.float)])
sc = SC({'positions': np.zeros((num,), dtype=pos_dt),
'status_codes': np.zeros((num,), dtype=np.int16),
'windages': np.zeros((num,)),
})
# delta = np.zeros_like(sc['positions'])
wind = wind_from_values([(datetime(2016, 5, 10, 12, 0), 5, 45),
(datetime(2016, 5, 10, 12, 20), 6, 50),
(datetime(2016, 5, 10, 12, 40), 7, 55),
])
wm = WindMover(wind)
# in time span, this should work:
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 12, 20))
# before timespan -- this should fail
with pytest.raises(RuntimeError):
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
# after timespan -- this should fail
with pytest.raises(RuntimeError):
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 12, 50))
# # test the message:
# try:
# wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
# except RuntimeError as err:
try:
wm.prepare_for_model_step(sc, 600, datetime(2016, 5, 10, 11, 50))
except RuntimeError as err:
msg = err.args[0]
assert "No available data" in msg
assert "WindMover" in msg
assert "2016-05-10 11:50:00" in msg
assert "2016-05-10 12:00:00" in msg
assert "2016-05-10 12:40:00" in msg
