Python WindMover.prepare_for_model_step方法代码示例

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
def test_active():
    """ test that mover must be both active and on to get movement """

    time_step = 15 * 60  # seconds

    start_pos = (3., 6., 0.)
    rel_time = datetime(2012, 8, 20, 13)  # yyyy/month/day/hr/min/sec

    sc = sample_sc_release(5, start_pos, rel_time)

    # value is given as (r,theta)

    time_val = np.zeros((1, ), dtype=datetime_value_2d)
    time_val['time'] = np.datetime64(rel_time.isoformat())
    time_val['value'] = (2., 25.)

    wm = WindMover(environment.Wind(timeseries=time_val,
                   units='meter per second'), on=False)

    wm.prepare_for_model_run()
    wm.prepare_for_model_step(sc, time_step, rel_time)
    delta = wm.get_move(sc, time_step, rel_time)
    wm.model_step_is_done()
    assert wm.active == False
    assert np.all(delta == 0)  # model_time + time_step = active_start

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
    def test_variable_wind_after_model_time(self):
        '''
            test to make sure the wind mover is behaving properly with
            out-of-bounds winds.
            A variable wind should not extrapolate if it is out of bounds,
            so prepare_for_model_step() should fail with an exception
            in this case.
        '''
        wind_time = datetime(2012, 8, 21, 13)  # one day after model time

        time_series = (np.zeros((3, ), dtype=datetime_value_2d)
                       .view(dtype=np.recarray))
        time_series.time = [sec_to_date(date_to_sec(wind_time) +
                                        self.time_step * i)
                            for i in range(3)]
        time_series.value = np.array(((2., 25.), (2., 25.), (2., 25.)))

        wind = Wind(timeseries=time_series.reshape(3),
                    units='meter per second')

        wm = WindMover(wind)
        wm.prepare_for_model_run()

        for ix in range(2):
            curr_time = sec_to_date(date_to_sec(self.model_time) +
                                    self.time_step * ix)

            with raises(RuntimeError):
                wm.prepare_for_model_step(self.sc, self.time_step, curr_time)

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
def test_prepare_for_model_step():
    """
    explicitly test to make sure windages are being updated for persistence
    != 0 and windages are not being changed for persistance == -1
    """
    time_step = 15 * 60  # seconds
    model_time = datetime(2012, 8, 20, 13)  # yyyy/month/day/hr/min/sec
    sc = sample_sc_release(5, (3., 6., 0.), model_time)
    sc['windage_persist'][:2] = -1
    wind = Wind(timeseries=np.array((model_time, (2., 25.)),
                                    dtype=datetime_value_2d).reshape(1),
                units='meter per second')

    wm = WindMover(wind)
    wm.prepare_for_model_run()

    for ix in range(2):
        curr_time = sec_to_date(date_to_sec(model_time) + time_step * ix)
        old_windages = np.copy(sc['windages'])
        wm.prepare_for_model_step(sc, time_step, curr_time)

        mask = [sc['windage_persist'] == -1]
        assert np.all(sc['windages'][mask] == old_windages[mask])

        mask = [sc['windage_persist'] > 0]
        assert np.all(sc['windages'][mask] != old_windages[mask])

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
    def test_constant_wind_after_model_time(self):
        '''
            test to make sure the wind mover is behaving properly with
            out-of-bounds winds.
            A constant wind should extrapolate if it is out of bounds,
            so prepare_for_model_step() should not fail.

            We are testing that the wind extrapolates properly, so the
            windages should be updated in the same way as the in-bounds test
        '''
        wind_time = datetime(2012, 8, 21, 13)  # one day after model time

        wind = Wind(timeseries=np.array((wind_time, (2., 25.)),
                                        dtype=datetime_value_2d).reshape(1),
                    units='meter per second')

        wm = WindMover(wind)
        wm.prepare_for_model_run()

        for ix in range(2):
            curr_time = sec_to_date(date_to_sec(self.model_time) +
                                    self.time_step * ix)
            print 'curr_time = ', curr_time

            old_windages = np.copy(self.sc['windages'])
            wm.prepare_for_model_step(self.sc, self.time_step, curr_time)

            mask = self.sc['windage_persist'] == -1
            assert np.all(self.sc['windages'][mask] == old_windages[mask])

            mask = self.sc['windage_persist'] > 0
            assert np.all(self.sc['windages'][mask] != old_windages[mask])

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
def test_windage_index():
    """
    A very simple test to make sure windage is set for the correct sc
    if staggered release
    """

    sc = SpillContainer()
    rel_time = datetime(2013, 1, 1, 0, 0)
    timestep = 30
    for i in range(2):
        spill = point_line_release_spill(num_elements=5,
                                start_position=(0., 0., 0.),
                                release_time=rel_time + i * timedelta(hours=1),
                                element_type=floating(windage_range=(i * .01 +
                                                        .01, i * .01 + .01),
                                                      windage_persist=900)
                                )
        sc.spills.add(spill)

    windage = {'windages': array_types.windages,
               'windage_range': array_types.windage_range,
               'windage_persist': array_types.windage_persist}
    sc.prepare_for_model_run(array_types=windage)
    sc.release_elements(timestep, rel_time)
    wm = WindMover(environment.ConstantWind(5, 0))
    wm.prepare_for_model_step(sc, timestep, rel_time)
    wm.model_step_is_done()  # need this to toggle _windage_is_set_flag

    def _check_index(sc):
        '''
        internal function for doing the test after windage is set
        - called twice so made a function
        '''

        # only 1st sc is released

        for sp in sc.spills:
            mask = sc.get_spill_mask(sp)
            if np.any(mask):
                assert np.all(sc['windages'][mask] ==
                              (sp.element_type.initializers["windages"].
                              windage_range[0]))

    # only 1st spill is released
    _check_index(sc)  # 1st ASSERT

    sc.release_elements(timestep, rel_time + timedelta(hours=1))
    wm.prepare_for_model_step(sc, timestep, rel_time)
    _check_index(sc)  # 2nd ASSERT

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
def test_timespan():
    """
    Ensure the active flag is being set correctly and checked,
    such that if active=False, the delta produced by get_move = 0
    """
    time_step = 15 * 60  # seconds

    start_pos = (3., 6., 0.)
    rel_time = datetime(2012, 8, 20, 13)  # yyyy/month/day/hr/min/sec

    sc = sample_sc_release(5, start_pos, rel_time)

    # value is given as (r,theta)
    model_time = rel_time
    time_val = np.zeros((1, ), dtype=datetime_value_2d)
    time_val['time'] = rel_time
    time_val['value'] = (2., 25.)

    wm = WindMover(Wind(timeseries=time_val,
                        units='meter per second'),
                   active_range=(model_time + timedelta(seconds=time_step),
                                 InfDateTime('inf')))

    wm.prepare_for_model_run()
    wm.prepare_for_model_step(sc, time_step, model_time)

    delta = wm.get_move(sc, time_step, model_time)
    wm.model_step_is_done()

    assert wm.active is False
    assert np.all(delta == 0)  # model_time + time_step = active_start

    wm.active_range = (model_time - timedelta(seconds=time_step / 2),
                       InfDateTime('inf'))
    wm.prepare_for_model_step(sc, time_step, model_time)

    delta = wm.get_move(sc, time_step, model_time)
    wm.model_step_is_done()

    assert wm.active is True
    print '''\ntest_timespan delta \n{0}'''.format(delta)
    assert np.all(delta[:, :2] != 0)  # model_time + time_step > active_start

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
    def test_variable_wind_after_model_time_with_extrapolation(self):
        '''
            test to make sure the wind mover is behaving properly with
            out-of-bounds winds.
            A variable wind can extrapolate if it is configured to do so,
            so prepare_for_model_step() should succeed in this case.

            We are testing that the wind extrapolates properly, so the
            windages should be updated in the same way as the in-bounds test
        '''
        wind_time = datetime(2012, 8, 21, 13)  # one day after model time

        time_series = (np.zeros((3, ), dtype=datetime_value_2d)
                       .view(dtype=np.recarray))
        time_series.time = [sec_to_date(date_to_sec(wind_time) +
                                        self.time_step * i)
                            for i in range(3)]
        time_series.value = np.array(((2., 25.), (2., 25.), (2., 25.)))

        wind = Wind(timeseries=time_series.reshape(3),
                    extrapolation_is_allowed=True,
                    units='meter per second')

        wm = WindMover(wind)
        wm.prepare_for_model_run()

        for ix in range(2):
            curr_time = sec_to_date(date_to_sec(self.model_time) +
                                    self.time_step * ix)

            old_windages = np.copy(self.sc['windages'])
            wm.prepare_for_model_step(self.sc, self.time_step, curr_time)

            mask = self.sc['windage_persist'] == -1
            assert np.all(self.sc['windages'][mask] == old_windages[mask])

            mask = self.sc['windage_persist'] > 0
            assert np.all(self.sc['windages'][mask] != old_windages[mask])

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
    def test_windages_updated(self):
        '''
            explicitly test to make sure:
            - windages are being updated for persistence != 0 and
            - windages are not being changed for persistance == -1
        '''
        wind = Wind(timeseries=np.array((self.model_time, (2., 25.)),
                                        dtype=datetime_value_2d).reshape(1),
                    units='meter per second')

        wm = WindMover(wind)
        wm.prepare_for_model_run()

        for ix in range(2):
            curr_time = sec_to_date(date_to_sec(self.model_time) +
                                    self.time_step * ix)
            old_windages = np.copy(self.sc['windages'])
            wm.prepare_for_model_step(self.sc, self.time_step, curr_time)

            mask = self.sc['windage_persist'] == -1
            assert np.all(self.sc['windages'][mask] == old_windages[mask])

            mask = self.sc['windage_persist'] > 0
            assert np.all(self.sc['windages'][mask] != old_windages[mask])

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
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

# 需要导入模块: from gnome.movers import WindMover [as 别名]
# 或者: from gnome.movers.WindMover import prepare_for_model_step [as 别名]
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