def test_kymograph_collection(tmp_path):
"""test making kymographs for field collections"""
# create some storage
field = FieldCollection([
ScalarField(UnitGrid(8), label="a"),
ScalarField(UnitGrid(8), label="b")
])
with get_memory_storage(field) as storage:
for i in range(8):
field.data = i
storage.append(field, i)
# create single kymograph
path = tmp_path / "test1.png"
plotting.plot_kymograph(storage,
field_index=1,
colorbar=True,
transpose=True,
filename=path)
assert path.stat().st_size > 0
# create multiple kymographs
path = tmp_path / "test2.png"
plotting.plot_kymographs(storage, filename=path)
assert path.stat().st_size > 0
def test_storage_apply(tmp_path):
""" test the apply function of StorageBase """
grid = UnitGrid([2])
field = ScalarField(grid)
storage_classes = {"None": None, "MemoryStorage": MemoryStorage}
if module_available("h5py"):
file_path = tmp_path / "test_storage_apply.hdf5"
storage_classes["FileStorage"] = functools.partial(
FileStorage, file_path)
s1 = MemoryStorage()
s1.start_writing(field, info={"b": 2})
s1.append(field.copy(data=np.array([0, 1])), 0)
s1.append(field.copy(data=np.array([1, 2])), 1)
s1.end_writing()
for name, storage_cls in storage_classes.items():
out = None if storage_cls is None else storage_cls()
s2 = s1.apply(lambda x: x + 1, out=out)
assert storage_cls is None or s2 is out
assert len(s2) == 2
np.testing.assert_allclose(s2.times, s1.times)
assert s2[0] == ScalarField(grid, [1, 2]), name
assert s2[1] == ScalarField(grid, [2, 3]), name
# test empty storage
s1 = MemoryStorage()
s2 = s1.apply(lambda x: x + 1)
assert len(s2) == 0
def test_pde_critical_input():
"""test some wrong input and edge cases"""
# test whether reserved symbols can be used as variables
grid = grids.UnitGrid([4])
eq = PDE({"E": 1})
res = eq.solve(ScalarField(grid), t_range=2)
np.testing.assert_allclose(res.data, 2)
with pytest.raises(ValueError):
PDE({"t": 1})
eq = PDE({"u": 1})
assert eq.expressions == {"u": "1.0"}
with pytest.raises(ValueError):
eq.evolution_rate(FieldCollection.scalar_random_uniform(2, grid))
eq = PDE({"u": 1, "v": 2})
assert eq.expressions == {"u": "1.0", "v": "2.0"}
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"u": "a"})
with pytest.raises(RuntimeError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"x": "x"})
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField(grid))
def test_vector_from_scalars():
"""test how to compile vector fields from scalar fields"""
g = UnitGrid([1, 2])
s1 = ScalarField(g, [[0, 1]])
s2 = ScalarField(g, [[2, 3]])
v = VectorField.from_scalars([s1, s2], label="test")
assert v.label == "test"
np.testing.assert_equal(v.data, [[[0, 1]], [[2, 3]]])
with pytest.raises(ValueError):
VectorField.from_scalars([s1, s2, s1])
def test_collection_plot(tmp_path):
"""test Simple simulation"""
# create some data
field = FieldCollection([
ScalarField(UnitGrid([8, 8]), label="first"),
ScalarField(UnitGrid([8, 8]))
])
with get_memory_storage(field) as storage:
storage.append(field)
path = tmp_path / "test_collection_plot.png"
plotting.plot_magnitudes(storage, filename=path)
assert path.stat().st_size > 0
def test_scalar_arithmetics():
"""test simple arithmetics involving scalar fields"""
grid = UnitGrid([3, 4])
s = ScalarField(grid, data=2)
v = VectorField.random_uniform(grid)
for f in [v, FieldCollection([v])]:
f.data = s
assert f.data.shape == (2, 3, 4)
np.testing.assert_allclose(f.data, 2)
f += s
np.testing.assert_allclose(f.data, 4)
np.testing.assert_allclose((f + s).data, 6)
np.testing.assert_allclose((s + f).data, 6)
f -= s
np.testing.assert_allclose((f - s).data, 0)
np.testing.assert_allclose((s - f).data, 0)
f *= s
np.testing.assert_allclose(f.data, 4)
np.testing.assert_allclose((f * s).data, 8)
np.testing.assert_allclose((s * f).data, 8)
f /= s
np.testing.assert_allclose((f / s).data, 1)
with pytest.raises(TypeError):
s / f
with pytest.raises(TypeError):
s /= f
with pytest.raises(TypeError):
s *= f
def test_field_type_guessing():
""" test the ability to guess the field type """
for cls in [ScalarField, VectorField, Tensor2Field]:
grid = UnitGrid([3])
field = cls.random_normal(grid)
s = MemoryStorage()
s.start_writing(field)
s.append(field, 0)
s.append(field, 1)
# delete information
s._field = None
s.info = {}
assert not s.has_collection
assert len(s) == 2
assert s[0] == field
field = FieldCollection([ScalarField(grid), VectorField(grid)])
s = MemoryStorage()
s.start_writing(field)
s.append(field, 0)
assert s.has_collection
# delete information
s._field = None
s.info = {}
with pytest.raises(RuntimeError):
s[0]
def get_phase_field(self,
grid: GridBase,
*,
vmin: float = 0,
vmax: float = 1,
label: str = None) -> ScalarField:
"""Creates an image of the droplet on the `grid`
Args:
grid (:class:`~pde.grids.base.GridBase`):
The grid used for discretizing the droplet phase field
vmin (float):
Minimal value the phase field will attain (far away from droplet)
vmax (float):
Maximal value the phase field will attain (inside the droplet)
label (str):
The label associated with the returned scalar field
Returns:
:class:`~pde.fields.ScalarField`: A scalar field
representing the droplet
"""
data = self._get_phase_field(grid)
data = vmin + (vmax - vmin) * data # scale data
return ScalarField(grid, data=data, label=label)
def test_memory_storage():
"""test methods specific to memory storage"""
sf = ScalarField(UnitGrid([1]))
s1 = MemoryStorage()
s1.start_writing(sf)
sf.data = 0
s1.append(sf, 0)
sf.data = 2
s1.append(sf, 1)
s2 = MemoryStorage()
s2.start_writing(sf)
sf.data = 1
s2.append(sf, 0)
sf.data = 3
s2.append(sf, 1)
# test from_fields
s3 = MemoryStorage.from_fields(s1.times, [s1[0], s1[1]])
assert s3.times == s1.times
np.testing.assert_allclose(s3.data, s1.data)
# test from_collection
s3 = MemoryStorage.from_collection([s1, s2])
assert s3.times == s1.times
np.testing.assert_allclose(np.ravel(s3.data), np.arange(4))
def get_phasefield(self,
grid: GridBase = None,
label: Optional[str] = None) -> ScalarField:
"""create a phase field representing a list of droplets
Args:
grid (:class:`pde.grids.base.GridBase`):
The grid on which the phase field is created. If omitted, the
grid associated with the emulsion is used.
label (str):
Optional label for the returned scalar field
Returns:
:class:`~pde.fields.scalar.ScalarField`: the actual phase field
"""
if grid is None:
grid = self.grid
if grid is None:
raise RuntimeError("Grid needs to be specified")
if len(self) == 0:
return ScalarField(grid)
else:
result: ScalarField = self[0].get_phase_field(grid, label=label)
for d in self[1:]:
result += d.get_phase_field(grid)
np.clip(result.data, 0, 1, out=result.data)
return result
def test_pde_wrong_input():
"""test some wrong input"""
with pytest.raises(ValueError):
PDE({"t": 1})
with pytest.raises(ValueError):
PDE({"E": 1})
with pytest.raises(ValueError):
PDE({"E": 1, "t": 0})
grid = grids.UnitGrid([4])
eq = PDE({"u": 1})
assert eq.expressions == {"u": "1.0"}
with pytest.raises(ValueError):
eq.evolution_rate(FieldCollection.scalar_random_uniform(2, grid))
eq = PDE({"u": 1, "v": 2})
assert eq.expressions == {"u": "1.0", "v": "2.0"}
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"u": "a"})
with pytest.raises(RuntimeError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"x": "x"})
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField(grid))
def test_pde_noise(backend):
"""test noise operator on PDE class"""
grid = grids.UnitGrid([64, 64])
state = FieldCollection([ScalarField(grid), ScalarField(grid)])
eq = PDE({"a": 0, "b": 0}, noise=0.5)
res = eq.solve(state, t_range=1, backend=backend, dt=1, tracker=None)
assert res.data.std() == pytest.approx(0.5, rel=0.1)
eq = PDE({"a": 0, "b": 0}, noise=[0.01, 2.0])
res = eq.solve(state, t_range=1, backend=backend, dt=1)
assert res.data[0].std() == pytest.approx(0.01, rel=0.1)
assert res.data[1].std() == pytest.approx(2.0, rel=0.1)
with pytest.raises(ValueError):
eq = PDE({"a": 0}, noise=[0.01, 2.0])
eq.solve(ScalarField(grid), t_range=1, backend=backend, dt=1, tracker=None)
def test_pde_time_dependent_bcs(backend):
"""test PDE with time-dependent BCs"""
field = ScalarField(grids.UnitGrid([3]))
eq = PDE({"c": "laplace(c)"}, bc={"value_expression": "Heaviside(t - 1.5)"})
storage = MemoryStorage()
eq.solve(field, t_range=10, dt=1e-2, backend=backend, tracker=storage.tracker(1))
np.testing.assert_allclose(storage[1].data, 0)
np.testing.assert_allclose(storage[-1].data, 1, rtol=1e-3)
def test_pde_spatial_args(backend):
"""test PDE with spatial dependence"""
field = ScalarField(grids.UnitGrid([2]))
eq = PDE({"a": "x"})
rhs = eq.make_pde_rhs(field, backend=backend)
np.testing.assert_allclose(rhs(field.data, 0.0), np.array([0.5, 1.5]))
# test combination of spatial dependence and differential oeprators
eq = PDE({"a": "dot(gradient(x), gradient(a))"})
rhs = eq.make_pde_rhs(field, backend=backend)
np.testing.assert_allclose(rhs(field.data, 0.0), np.array([0.0, 0.0]))
# test invalid spatial dependence
eq = PDE({"a": "x + y"})
with pytest.raises(RuntimeError):
rhs = eq.make_pde_rhs(field, backend=backend)
rhs(field.data, 0.0)
def test_kymograph_single(tmp_path):
""" test making kymographs for single fields """
# create some storage
field = ScalarField(UnitGrid(8))
with get_memory_storage(field) as storage:
for i in range(8):
storage.append(field.copy(data=i), i)
# create single kymograph
path = tmp_path / "test1.png"
plotting.plot_kymograph(storage,
colorbar=True,
transpose=True,
filename=path)
assert path.stat().st_size > 0
# create multiple kymographs
path = tmp_path / "test2.png"
plotting.plot_kymographs(storage, filename=path)
assert path.stat().st_size > 0
def test_pde_consts():
"""test using the consts argument in PDE"""
field = ScalarField(grids.UnitGrid([3]), 1)
eq = PDE({"a": "b"}, consts={"b": 2})
np.testing.assert_allclose(eq.evolution_rate(field).data, 2)
eq = PDE({"a": "b**2"}, consts={"b": field})
np.testing.assert_allclose(eq.evolution_rate(field).data, field.data)
eq = PDE({"a": "laplace(b)"}, consts={"b": field})
np.testing.assert_allclose(eq.evolution_rate(field).data, 0)
eq = PDE({"a": "laplace(b)"}, consts={"b": 3})
with pytest.raises(Exception):
eq.evolution_rate(field)
eq = PDE({"a": "laplace(b)"}, consts={"b": field.data})
with pytest.raises(Exception):
eq.evolution_rate(field)
def test_storage_write(tmp_path):
"""test simple memory storage"""
dim = 5
grid = UnitGrid([dim])
field = ScalarField(grid)
storage_classes = {"MemoryStorage": MemoryStorage}
if module_available("h5py"):
file_path = tmp_path / "test_storage_write.hdf5"
storage_classes["FileStorage"] = functools.partial(
FileStorage, file_path)
for name, storage_cls in storage_classes.items():
storage = storage_cls(info={"a": 1})
storage.start_writing(field, info={"b": 2})
field.data = np.arange(dim)
storage.append(field, 0)
field.data = np.arange(dim)
storage.append(field, 1)
storage.end_writing()
assert not storage.has_collection
np.testing.assert_allclose(storage.times, np.arange(2))
for f in storage:
np.testing.assert_array_equal(f.data, np.arange(dim))
for i in range(2):
np.testing.assert_array_equal(storage[i].data, np.arange(dim))
assert {"a": 1, "b": 2}.items() <= storage.info.items()
storage = storage_cls()
storage.clear()
for i in range(3):
storage.start_writing(field)
field.data = np.arange(dim) + i
storage.append(field, i)
storage.end_writing()
np.testing.assert_allclose(storage.times,
np.arange(3),
err_msg="storage class: " + name)
def test_storing_extract_range(tmp_path):
"""test methods specific to FieldCollections in memory storage"""
sf = ScalarField(UnitGrid([1]))
storage_classes = {"MemoryStorage": MemoryStorage}
if module_available("h5py"):
file_path = tmp_path / "test_storage_write.hdf5"
storage_classes["FileStorage"] = functools.partial(
FileStorage, file_path)
for storage_cls in storage_classes.values():
# store some data
s1 = storage_cls()
s1.start_writing(sf)
sf.data = np.array([0])
s1.append(sf, 0)
sf.data = np.array([2])
s1.append(sf, 1)
s1.end_writing()
np.testing.assert_equal(s1[0].data, 0)
np.testing.assert_equal(s1[1].data, 2)
np.testing.assert_equal(s1[-1].data, 2)
np.testing.assert_equal(s1[-2].data, 0)
with pytest.raises(IndexError):
s1[2]
with pytest.raises(IndexError):
s1[-3]
# test extraction
s2 = s1.extract_time_range()
assert s2.times == list(s1.times)
np.testing.assert_allclose(s2.data, s1.data)
s3 = s1.extract_time_range(0.5)
assert s3.times == s1.times[:1]
np.testing.assert_allclose(s3.data, s1.data[:1])
s4 = s1.extract_time_range((0.5, 1.5))
assert s4.times == s1.times[1:]
np.testing.assert_allclose(s4.data, s1.data[1:])