def test_construction(self):
u = None
v = None
with pytest.raises(ValueError):
# mismatched data and dates length
dates = []
u = TimeSeriesProp(
'u', 'm/s', [datetime.datetime.now(),
datetime.datetime.now()], [
5,
])
u = TimeSeriesProp('u', 'm/s', [datetime.datetime.now()], [
5,
])
assert u is not None
assert u.name == 'u'
assert u.units == 'm/s'
v = None
with pytest.raises(ValueError):
v = TimeSeriesProp('v', 'nm/hr', [datetime.datetime.now()], [
5,
])
assert v is None
constant = TimeSeriesProp.constant('const', 'm/s', 5)
assert constant.data[0] == 5
assert all(constant.at(np.array((0, 0)), datetime.datetime.now()) == 5)
def __init__(self,
temperature=300.,
salinity=35.0,
sediment=.005,
fetch=0,
name='WaterConditions',
**kwargs):
'''
Assume units are SI for all properties. 'units' attribute assumes SI
by default. This can be changed, but initialization takes SI.
'''
if isinstance(temperature, (Number)):
self.temperature = TemperatureTS.constant(data=temperature)
elif isinstance(temperature, (EnvProp)):
self.temperature = temperature
else:
raise TypeError('Temperature is not an environment object or number')
if isinstance(salinity, (Number)):
self.salinity = TimeSeriesProp.constant(name='Salinity', units='psu', data=salinity)
elif isinstance(salinity, (EnvProp)):
self.salinity = salinity
else:
raise TypeError('Salinity is not an environment object or number')
if isinstance(sediment, (Number)):
self.sediment = TimeSeriesProp.constant(name='Sediment', units='kg/m^3', data=sediment)
elif isinstance(sediment, (EnvProp)):
self.sediment = sediment
else:
raise TypeError('Sediment is not an environment object or number')
# self.wave_height = wave_height
self.fetch = fetch
self.kinematic_viscosity = 0.000001
self.name = 'WaterConditions'
def test_at(self):
dates2 = np.array([
dt.datetime(2000, 1, 1, 0),
dt.datetime(2000, 1, 1, 2),
dt.datetime(2000, 1, 1, 4),
dt.datetime(2000, 1, 1, 6),
dt.datetime(2000, 1, 1, 8),
])
u_data = np.array([2., 4., 6., 8., 10.])
u = TimeSeriesProp(name='u', units='m/s', time=dates2, data=u_data)
corners = np.array(((1, 1), (2, 2)))
t1 = dt.datetime(1999, 12, 31, 23)
t2 = dt.datetime(2000, 1, 1, 0)
t3 = dt.datetime(2000, 1, 1, 1)
t4 = dt.datetime(2000, 1, 1, 8)
t5 = dt.datetime(2000, 1, 1, 9)
# No extrapolation. out of bounds time should fail
with pytest.raises(ValueError):
u.at(corners, t1)
assert (u.at(corners, t2) == np.array([2])).all()
assert (u.at(corners, t3) == np.array([3])).all()
assert (u.at(corners, t4) == np.array([10])).all()
with pytest.raises(ValueError):
u.at(corners, t5)
# turn extrapolation on
assert (u.at(corners, t1, extrapolate=True) == np.array([2])).all()
assert (u.at(corners, t5, extrapolate=True) == np.array([10])).all()
def __init__(self,
name=None,
units='K',
time=None,
data=None,
**kwargs):
if 'timeseries' in kwargs:
ts = kwargs['timeseries']
time = map(lambda e: e[0], ts)
data = np.array(map(lambda e: e[1], ts))
TimeSeriesProp.__init__(self, name, units, time, data=data)
def __init__(self,
name=None,
units='K',
time=None,
data=None,
**kwargs):
if 'timeseries' in kwargs:
ts = kwargs['timeseries']
time = map(lambda e: e[0], ts)
data = np.array(map(lambda e: e[1], ts))
TimeSeriesProp.__init__(self, name, units, time, data=data)
def __init__(self,
name=None,
units='kg/m^3',
temperature=None,
salinity=None):
if temperature is None or salinity is None or not isinstance(temperature, TemperatureTS) or not isinstance(salinity, SalinityTS):
raise ValueError('Must provide temperature and salinity time series Environment objects')
density_times = temperature.time if len(temperature.time.time) > len(salinity.time.time) else salinity.time
dummy_pt = np.array([[0, 0], ])
import gsw
from gnome import constants
data = [gsw.rho(salinity.at(dummy_pt, t), temperature.at(dummy_pt, t, units='C'), constants.atmos_pressure * 0.0001) for t in density_times.time]
TimeSeriesProp.__init__(self, name, units, time=density_times, data=data)
def test_unit_conversion(self):
u = TimeSeriesProp('u', 'm/s', [datetime.datetime.now()], [
5,
])
t = u.in_units('km/hr')
assert t.data is not u.data
assert round(t.data[0], 2) == 18.0
with pytest.raises(unit_conversion.NotSupportedUnitError):
# mismatched data and dates length
t = u.in_units('nm/hr')
def __init__(self,
name=None,
units='kg/m^3',
temperature=None,
salinity=None):
if temperature is None or salinity is None or not isinstance(temperature, TemperatureTS) or not isinstance(salinity, SalinityTS):
raise ValueError('Must provide temperature and salinity time series Environment objects')
density_times = temperature.time if len(temperature.time.time) > len(salinity.time.time) else salinity.time
dummy_pt = np.array([[0, 0], ])
import gsw
from gnome import constants
data = [gsw.rho(salinity.at(dummy_pt, t), temperature.at(dummy_pt, t, units='C'), constants.atmos_pressure * 0.0001) for t in density_times.time]
TimeSeriesProp.__init__(self, name, units, time=density_times, data=data)
def new_from_dict(cls, dict_):
varnames = dict_['varnames']
vs = []
for i, varname in enumerate(varnames):
vs.append(
TimeSeriesProp(name=varname,
units=dict_['units'],
time=dict_['time'],
data=dict_['data'][i]))
dict_.pop('data')
dict_['variables'] = vs
return super(VelocityTS, cls).new_from_dict(dict_)
def test_construction(self):
u = None
v = None
with pytest.raises(ValueError):
# mismatched data and dates length
u = TimeSeriesProp('u', 'm/s', dates, u_data)
assert u is None
u = TimeSeriesProp('u', 'm/s', dates2, u_data)
assert u is not None
assert u.name == 'u'
assert u.units == 'm/s'
print u.time == Time(dates2)
assert u.time == Time(dates2)
assert (u.data == u_data).all()
v = None
with pytest.raises(ValueError):
v = TimeSeriesProp('v', 'nm/hr', dates2, v_data)
assert v is None
def constant(cls,
name='',
speed=0,
direction=0,
units='m/s'):
"""
utility to create a constant wind "timeseries"
:param speed: speed of wind
:param direction: direction -- degrees True, direction wind is from
(degrees True)
:param units='m/s': units for speed, as a string, i.e. "knots", "m/s",
"cm/s", etc.
.. note::
The time for a constant wind timeseries is irrelevant. This
function simply sets it to datetime.now() accurate to hours.
"""
direction = direction * -1 - 90
u = speed * np.cos(direction * np.pi / 180)
v = speed * np.sin(direction * np.pi / 180)
u = TimeSeriesProp.constant('u', units, u)
v = TimeSeriesProp.constant('v', units, v)
return super(VelocityTS, cls).constant(name, units, variables=[u, v])
def __init__(self, angle=None, **kwargs):
"""
:param angle: scalar field of cell rotation angles (for rotated/distorted grids)
"""
if 'variables' in kwargs:
variables = kwargs['variables']
if len(variables) == 2:
variables.append(TimeSeriesProp(name='constant w', data=[0.0], time=Time.constant_time(), units='m/s'))
kwargs['variables'] = variables
if angle is None:
df = None
if kwargs.get('dataset', None) is not None:
df = kwargs['dataset']
elif kwargs.get('grid_file', None) is not None:
df = _get_dataset(kwargs['grid_file'])
if df is not None and 'angle' in df.variables.keys():
# Unrotated ROMS Grid!
self.angle = GriddedProp(name='angle', units='radians', time=None, grid=kwargs['grid'], data=df['angle'])
else:
self.angle = None
else:
self.angle = angle
super(VelocityGrid, self).__init__(**kwargs)
) # scale winds from 100-0% depending on ice coverage
return vels
else:
return self.wind_var.at(points, time, units, extrapolate)
if __name__ == "__main__":
import datetime as dt
dates = np.array([
dt.datetime(2000, 1, 1, 0),
dt.datetime(2000, 1, 1, 2),
dt.datetime(2000, 1, 1, 4)
])
u_data = np.array([3, 4, 5])
v_data = np.array([4, 3, 12])
u = TimeSeriesProp('u', 'm/s', dates, u_data)
v = TimeSeriesProp('v', 'm/s', dates, v_data)
print u.at(np.array([(1, 1), (1, 2)]), dt.datetime(2000, 1, 1, 1))
vprop = TSVectorProp('velocity', 'm/s', variables=[u, v])
print vprop.at(np.array([(1, 1), (1, 2)]), dt.datetime(2000, 1, 1, 3))
vel = VelocityTS('test_vel', variables=[u, v])
print vel.at(np.array([(1, 1), (1, 2)]), dt.datetime(2000, 1, 1, 3))
import pprint
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(vel.serialize())
pp.pprint(VelocityTS.deserialize(vel.serialize()))
def v():
return TimeSeriesProp(name='v', units='m/s', time=dates2, data=v_data)
def u():
return TimeSeriesProp(name='u', units='m/s', time=dates2, data=u_data)
