def test_annular():
sheet = generate_ring(10, 1, 2, R_vit=None, apical="in")
PlanarGeometry.update_all(sheet)
apical_length = sheet.edge_df.loc[sheet.apical_edges, "length"]
basal_length = sheet.edge_df.loc[sheet.basal_edges, "length"]
lateral_length = sheet.edge_df.loc[sheet.lateral_edges, "length"]
assert sheet.Nf == 10
assert sheet.Ne == 40
assert sheet.Nv == 20
assert_almost_equal(apical_length.mean(), 2 * sin(np.pi / 10))
assert_almost_equal(basal_length.mean(), 4 * sin(np.pi / 10))
assert_almost_equal(lateral_length.mean(), 1)
assert (np.linalg.norm(sheet.vert_df.loc[sheet.apical_verts, ["x", "y"]],
axis=1).mean() == 1)
assert (np.linalg.norm(sheet.vert_df.loc[sheet.basal_verts, ["x", "y"]],
axis=1).mean() == 2)
sheet = generate_ring(10, 1, 2, R_vit=None, apical="out")
PlanarGeometry.update_all(sheet)
apical_length = sheet.edge_df.loc[sheet.apical_edges, "length"]
basal_length = sheet.edge_df.loc[sheet.basal_edges, "length"]
lateral_length = sheet.edge_df.loc[sheet.lateral_edges, "length"]
assert_almost_equal(apical_length.mean(), 4 * sin(np.pi / 10))
assert_almost_equal(basal_length.mean(), 2 * sin(np.pi / 10))
assert (np.linalg.norm(sheet.vert_df.loc[sheet.apical_verts, ["x", "y"]],
axis=1).mean() == 2)
assert (np.linalg.norm(sheet.vert_df.loc[sheet.basal_verts, ["x", "y"]],
axis=1).mean() == 1)
def test_x_and_y_boundary_celldiv():
dsets = hdf5.load_datasets(
Path(stores.stores_dir) / "planar_periodic8x8.hf5")
specs = config.geometry.planar_sheet()
specs["settings"]["boundaries"] = {"x": [-0.1, 8.1], "y": [-0.1, 8.1]}
sheet = Sheet("periodic", dsets, specs)
coords = ["x", "y"]
draw_specs = config.draw.sheet_spec()
PlanarGeometry.update_all(sheet)
Nf = sheet.Nf
# arbitrarily choose a cells on x_boundary and y_boundary to divide
div_cell = sheet.face_df.index[(sheet.face_df["at_x_boundary"] == True)
&
(sheet.face_df["at_y_boundary"] == True)][0]
daughter = cell_division(sheet, div_cell, PlanarGeometry, angle=0.6)
assert sheet.validate()
assert sheet.Nf == Nf + 1
def test_relaxation_convergance():
# Here we relax a pre-counstructed periodic tissue object to its "periodic equilibrium" configuration
# this tissue object that is loaded is far away from equilibrium 6x6 is the "periodic" equilibrium
dsets = hdf5.load_datasets(Path(stores.stores_dir) / "planar_periodic8x8.hf5")
specs = config.geometry.planar_sheet()
specs["settings"]["boundaries"] = {"x": [-0.1, 8.1], "y": [-0.1, 8.1]}
initial_box_size = 8.2
sheet = Sheet("periodic", dsets, specs)
coords = ["x", "y"]
draw_specs = config.draw.sheet_spec()
PlanarGeometry.update_all(sheet)
solver = QSSolver(with_collisions=False, with_t1=True, with_t3=False)
nondim_specs = config.dynamics.quasistatic_plane_spec()
dim_model_specs = model.dimensionalize(nondim_specs)
sheet.update_specs(dim_model_specs, reset=True)
# epsilon is deviation of boundary between iterations
epsilon = 1.0
# max_dev is the max epsilon allowed for configuration to be in equilibrium
max_dev = 0.001
# i counts the number of solver iterations
i = 0
# loop ends if box size variation between iterations drops 10^-3
# loaded tissue is far away from periodic equilibrium L=8 and equilibrium is reached around 6.06
while np.abs(epsilon) > max_dev:
i += 1
if i == 1:
previous_box_size = 0
else:
previous_box_size = solution_result["x"][-1]
solution_result = solver.find_energy_min(
sheet, PlanarGeometry, model, periodic=True
)
epsilon = solution_result["x"][-1] - previous_box_size
# print(epsilon)
final_box_size = (
sheet.settings["boundaries"]["x"][1] - sheet.settings["boundaries"]["x"][0]
)
print("number of iterations " + str(i))
print("final box size " + str(final_box_size))
assert 6.06 - 0.1 < final_box_size < 6.06 + 0.1
def test_periodic_planar():
hdf_path = hdf5.load_datasets(
os.path.join(stores_dir, "planar_periodic8x8.hf5"))
specs = config.stores.planar_periodic8x8()
sheet = Sheet("periodic", hdf_path, specs)
PlanarGeometry.update_all(sheet)
assert sheet.edge_df.length.max() < 1.0
fsx = sheet.edge_df["fx"] - sheet.edge_df["sx"]
fsy = sheet.edge_df["fy"] - sheet.edge_df["sy"]
lai = (fsx**2 + fsy**2)**0.5
assert lai.max() < 0.7
assert sheet.face_df.area.max() < 1.2
assert sheet.face_df.area.min() > 0.8
sheet.update_specs(config.geometry.sheet_spec())
sheet = Sheet("2.5D", sheet.datasets, sheet.specs)
SheetGeometry.update_all(sheet)
assert sheet.edge_df.length.max() < 1.0
fsx = sheet.edge_df["fx"] - sheet.edge_df["sx"]
fsy = sheet.edge_df["fy"] - sheet.edge_df["sy"]
lai = (fsx**2 + fsy**2)**0.5
assert lai.max() < 0.7
assert sheet.face_df.area.max() < 1.2
assert sheet.face_df.area.min() > 0.8
def update_all(cls, eptm):
PlanarGeometry.update_all(eptm)
cls.update_lumen_volume(eptm)