def test_pseudo_interaction(runtime, dt):
# A linear field where advected particles are moving at
# 1 m/s in the longitudinal direction.
xdim, ydim = (10, 20)
Uflow = Field('U',
np.ones((ydim, xdim), dtype=np.float64),
lon=np.linspace(0., 1e3, xdim, dtype=np.float64),
lat=np.linspace(0., 1e3, ydim, dtype=np.float64))
Vflow = Field('V',
np.zeros((ydim, xdim), dtype=np.float64),
grid=Uflow.grid)
fieldset = FieldSet(Uflow, Vflow)
# Execute the advection kernel only
pset = ParticleSet(fieldset, pclass=ScipyParticle, lon=[2], lat=[2])
pset.execute(AdvectionRK4, runtime=runtime, dt=dt)
# Execute both the advection and interaction kernel.
pset2 = ParticleSet(fieldset,
pclass=ScipyInteractionParticle,
lon=[2],
lat=[2],
interaction_distance=1)
pyfunc_inter = pset2.InteractionKernel(ConstantMoveInteraction)
pset2.execute(AdvectionRK4,
pyfunc_inter=pyfunc_inter,
runtime=runtime,
dt=dt)
# Check to see whether they have moved as predicted.
assert np.all(pset.lon == pset2.lon)
assert np.all(pset2.lat == pset2.lon)
assert np.all(
pset2._collection.data["time"][0] == pset._collection.data["time"][0])
def test_concatenate_interaction_kernels(fieldset, mode):
lons = [0.0, 0.1, 0.25, 0.44]
lats = [0.0, 0.0, 0.0, 0.0]
# Distance in meters R_earth*0.2 degrees
interaction_distance = 6371000 * 0.2 * np.pi / 180
pset = ParticleSet(fieldset,
pclass=ptype[mode],
lon=lons,
lat=lats,
interaction_distance=interaction_distance)
pset.execute(DoNothing,
pyfunc_inter=pset.InteractionKernel(DummyMoveNeighbor) +
pset.InteractionKernel(DummyMoveNeighbor),
endtime=1.,
dt=1.)
# The kernel results are only applied after all interactionkernels
# have been executed, so we expect the result to be double the
# movement from executing the kernel once.
assert np.allclose(pset.lat, [0.2, 0.4, 0.1, 0.0], rtol=1e-5)
def test_neighbor_merge(fieldset, mode):
lons = [0.0, 0.1, 0.25, 0.44]
lats = [0.0, 0.0, 0.0, 0.0]
# Distance in meters R_earth*0.2 degrees
interaction_distance = 6371000 * 5.5 * np.pi / 180
pset = ParticleSet(fieldset,
pclass=MergeParticle,
lon=lons,
lat=lats,
interaction_distance=interaction_distance)
pyfunc_inter = (pset.InteractionKernel(NearestNeighborWithinRange) +
MergeWithNearestNeighbor)
pset.execute(DoNothing, pyfunc_inter=pyfunc_inter, runtime=3., dt=1.)
# After two steps, the particles should be removed.
assert len(pset) == 1
def test_asymmetric_attraction(fieldset, mode):
lons = [0.0, 0.1, 0.2]
lats = [0.0, 0.0, 0.0]
# Distance in meters R_earth*0.2 degrees
interaction_distance = 6371000 * 5.5 * np.pi / 180
pset = ParticleSet(fieldset,
pclass=AttractingParticle,
lon=lons,
lat=lats,
interaction_distance=interaction_distance,
attractor=[True, False, False])
pyfunc_inter = pset.InteractionKernel(AsymmetricAttraction)
pset.execute(DoNothing, pyfunc_inter=pyfunc_inter, runtime=3., dt=1.)
assert lons[1] > pset.lon[1]
assert lons[2] > pset.lon[2]
assert len(pset) == 3