def test_emulsion_two():
"""test an emulsions with two droplets"""
grid = UnitGrid([30])
e = Emulsion([DiffuseDroplet([10], 3, 1)], grid=grid)
e1 = Emulsion([DiffuseDroplet([20], 5, 1)], grid=grid)
e.extend(e1)
assert e
assert len(e) == 2
assert e == e.copy()
assert e is not e.copy()
assert e.interface_width == pytest.approx(1)
assert e.total_droplet_volume == pytest.approx(16)
dists = e.get_pairwise_distances()
np.testing.assert_array_equal(dists, np.array([[0, 10], [10, 0]]))
expect = {
"count": 2,
"radius_mean": 4,
"radius_std": 1,
"volume_mean": 8,
"volume_std": 2,
}
assert e.get_size_statistics() == expect
np.testing.assert_array_equal(e.get_neighbor_distances(False), np.array([10, 10]))
np.testing.assert_array_equal(e.get_neighbor_distances(True), np.array([2, 2]))
def test_emulsion_plotting():
"""test plotting emulsions"""
# 1d emulsion
e1 = Emulsion([DiffuseDroplet([1], 10, 0.5)] * 2)
with pytest.raises(NotImplementedError):
e1.plot()
# 2d emulsion
field = ScalarField(UnitGrid([10, 10], periodic=True))
es = [
Emulsion([DiffuseDroplet([0, 1], 10, 0.5)] * 2),
Emulsion([droplets.PerturbedDroplet2D([0, 1], 3, 1, [1, 2, 3, 4])]),
]
for e2 in es:
e2.plot()
e2.plot(field=field)
# 3d emulsion
field = ScalarField(UnitGrid([5, 5, 5], periodic=True))
e3 = Emulsion([DiffuseDroplet([0, 1, 2], 10, 0.5)] * 2)
e3.plot()
e3.plot(field=field)
e3 = Emulsion([droplets.PerturbedDroplet3D([0, 1, 2], 3, 1, [1, 2, 3, 4, 5, 6])])
with pytest.raises(NotImplementedError):
e3.plot()
with pytest.raises(NotImplementedError):
Emulsion().plot()
def test_timecourse_io(tmp_path):
"""test writing and reading emulsions time courses"""
path = tmp_path / "test_timecourse_io.hdf5"
e1 = Emulsion()
e2 = Emulsion([DiffuseDroplet([0, 1], 10, 0.5)] * 2)
tc1 = emulsions.EmulsionTimeCourse([e1, e2], times=[0, 10])
tc1.to_file(path)
tc2 = emulsions.EmulsionTimeCourse.from_file(path, progress=False)
assert tc1.times == tc2.times
assert tc1.emulsions == tc2.emulsions
assert len(tc2) == 2
def test_emulsion_io(tmp_path):
"""test writing and reading emulsions"""
path = tmp_path / "test_emulsion_io.hdf5"
es = [
Emulsion(),
Emulsion([DiffuseDroplet([0, 1], 10, 0.5)] * 2),
Emulsion([droplets.PerturbedDroplet2D([0, 1], 3, 1, [1, 2, 3])]),
]
for e1 in es:
e1.to_file(path)
e2 = Emulsion.from_file(path)
assert e1 == e2
def test_emulsion_incompatible():
"""test incompatible droplets in an emulsion"""
# different type
d1 = SphericalDroplet([1], 2)
d2 = DiffuseDroplet([1], 2, 1)
e = Emulsion([d1, d2])
assert len(e) == 2
with pytest.raises(TypeError):
e.data
# same type
d1 = SphericalDroplet([1], 2)
d2 = SphericalDroplet([1, 2], 2)
with pytest.raises(ValueError):
e = Emulsion([d1, d2])
def test_emulsion_single():
"""test an emulsions with a single droplet"""
e = Emulsion([], grid=UnitGrid([2]))
e.append(DiffuseDroplet([10], 3, 1))
assert e
assert len(e) == 1
assert e == e.copy()
assert e is not e.copy()
assert e.interface_width == pytest.approx(1)
assert e.total_droplet_volume == pytest.approx(6)
dists = e.get_pairwise_distances()
np.testing.assert_array_equal(dists, np.zeros((1, 1)))
expect = {
"count": 1,
"radius_mean": 3,
"radius_std": 0,
"volume_mean": 6,
"volume_std": 0,
}
assert e.get_size_statistics() == expect
for b in [True, False]:
np.testing.assert_array_equal(e.get_neighbor_distances(b), np.array([np.nan]))
#!/usr/bin/env python3 from droplets import DiffuseDroplet, Emulsion, SphericalDroplet # construct two droplets drop1 = SphericalDroplet(position=[0, 0], radius=2) drop2 = DiffuseDroplet(position=[6, 8], radius=3, interface_width=1) # check whether they overlap print(drop1.overlaps(drop2)) # prints False # construct an emulsion and query it e = Emulsion([drop1, drop2]) e.get_size_statistics()
#!/usr/bin/env python3
import numpy as np
from droplets import DiffuseDroplet, Emulsion
# create 10 random droplets
droplets = [
DiffuseDroplet(
position=np.random.uniform(0, 100, 2),
radius=np.random.uniform(5, 10),
interface_width=1,
) for _ in range(10)
]
# remove overlapping droplets in emulsion and plot it
emulsion = Emulsion(droplets)
emulsion.remove_overlapping()
emulsion.plot()