def test_update_specs():
class BarrierElasticity(effectors.AbstractEffector):
"""
Barrier use to maintain the tissue integrity.
"""
dimensions = units.line_elasticity
magnitude = "barrier_elasticity"
label = "Barrier elasticity"
element = "vert"
specs = {
"vert": {"barrier_elasticity": 1.2, "is_active": 1, "delta_rho": 0.0}
} # distance to a barrier membrane
@staticmethod
def energy(eptm):
return eptm.vert_df.eval("delta_rho**2 * barrier_elasticity/2")
@staticmethod
def gradient(eptm):
grad = np.zeros((eptm.Nv, 3))
grad.columns = ["g" + c for c in eptm.coords]
return grad, None
model = factory.model_factory(
[
BarrierElasticity,
effectors.LineTension,
effectors.FaceAreaElasticity,
effectors.FaceContractility,
]
)
sheet_dsets, specs = three_faces_sheet()
sheet = Sheet("test", sheet_dsets, specs)
sheet.update_specs(model.specs)
assert sheet.vert_df.loc[0, "barrier_elasticity"] == 1.2
def test_sheet_view(self):
self.sheet = Sheet("test", *three_faces_sheet())
self.sheet.vert_df["rand"] = np.linspace(
0.0, 1.0, num=self.sheet.vert_df.shape[0]
)
cmap = plt.cm.get_cmap("viridis")
color_cmap = cmap(self.sheet.vert_df.rand)
self.draw_specs["vert"]["color"] = color_cmap
self.draw_specs["vert"]["alpha"] = 0.5
self.draw_specs["vert"]["s"] = 500
self.sheet.face_df["col"] = np.linspace(
0.0, 1.0, num=self.sheet.face_df.shape[0]
)
self.draw_specs["face"]["color"] = self.sheet.face_df["col"]
self.draw_specs["face"]["visible"] = True
self.draw_specs["face"]["alpha"] = 0.5
self.sheet.edge_df["rand"] = np.linspace(
0.0, 1.0, num=self.sheet.edge_df.shape[0]
)[::-1]
self.draw_specs["edge"]["visible"] = True
self.draw_specs["edge"]["color"] = self.sheet.edge_df["rand"] # [0, 0, 0, 1]
self.draw_specs["edge"]["alpha"] = 1.0
self.draw_specs["edge"]["color_range"] = 0, 3
self.draw_specs["edge"]["width"] = 1.0 * np.linspace(
0.0, 1.0, num=self.sheet.edge_df.shape[0]
)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert len(ax.collections) == 3
assert ax.collections[0].get_edgecolors().shape == (13, 4)
assert ax.collections[1].get_edgecolors().shape == (18, 4)
assert ax.collections[2].get_edgecolors().shape == (0, 4)
assert ax.collections[2].get_facecolors().shape == (3, 4)
def test_upcast_ndarray():
datasets_2d, specs = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d)
eptm = Epithelium("3faces_3D", datasets, specs)
data = np.arange(eptm.Nv * 3).reshape((eptm.Nv, 3))
assert eptm.upcast_srce(data).shape == (eptm.Ne, 3)
def test_polygons():
datasets_2d, specs = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d)
eptm = Epithelium("3faces_3D", datasets, specs)
eptm_2d = Epithelium("3faces_2D", datasets_2d, specs)
dict_expected_res = {
0: [
[0.0, 0.0, 0.0],
[1.0, 0.0, 0.0],
[1.5, 0.86599999999999999, 0.0],
[1.0, 1.732, 0.0],
[0.0, 1.732, 0.0],
[-0.5, 0.86599999999999999, 0.0],
],
1: [
[0.0, 0.0, 0.0],
[-0.5, 0.86599999999999999, 0.0],
[-1.5, 0.86599999999999999, 0.0],
[-2.0, 0.0, 0.0],
[-1.5, -0.86599999999999999, 0.0],
[-0.5, -0.86599999999999999, 0.0],
],
2: [
[0.0, 0.0, 0.0],
[-0.5, -0.86599999999999999, 0.0],
[0.0, -1.732, 0.0],
[1.0, -1.732, 0.0],
[1.5, -0.86599999999999999, 0.0],
[1.0, 0.0, 0.0],
],
3: [
[0.33333333333333331, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666666666666666, 0.28866666666666663, 0.0],
[0.0, 0.57733333333333325, 0.0],
[0.33333333333333331, 0.57733333333333325, 0.0],
[0.5, 0.28866666666666663, 0.0],
],
4: [
[-0.16666666666666666, 0.28866666666666663, 0.0],
[0.0, 0.0, 0.0],
[-0.16666666666666666, -0.28866666666666663, 0.0],
[-0.5, -0.28866666666666663, 0.0],
[-0.66666666666666663, 0.0, 0.0],
[-0.5, 0.28866666666666663, 0.0],
],
5: [
[-0.16666666666666666, -0.28866666666666663, 0.0],
[0.0, 0.0, 0.0],
[0.33333333333333331, 0.0, 0.0],
[0.5, -0.28866666666666663, 0.0],
[0.33333333333333331, -0.57733333333333325, 0.0],
[0.0, -0.57733333333333325, 0.0],
],
6: [
[1.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.33333333333333331, 0.0, 0.0],
],
7: [
[1.5, 0.86599999999999999, 0.0],
[1.0, 0.0, 0.0],
[0.33333333333333331, 0.0, 0.0],
[0.5, 0.28866666666666663, 0.0],
],
8: [
[1.0, 1.732, 0.0],
[1.5, 0.86599999999999999, 0.0],
[0.5, 0.28866666666666663, 0.0],
[0.33333333333333331, 0.57733333333333325, 0.0],
],
9: [
[0.0, 1.732, 0.0],
[1.0, 1.732, 0.0],
[0.33333333333333331, 0.57733333333333325, 0.0],
[0.0, 0.57733333333333325, 0.0],
],
10: [
[-0.5, 0.86599999999999999, 0.0],
[0.0, 1.732, 0.0],
[0.0, 0.57733333333333325, 0.0],
[-0.16666666666666666, 0.28866666666666663, 0.0],
],
11: [
[0.0, 0.0, 0.0],
[-0.5, 0.86599999999999999, 0.0],
[-0.16666666666666666, 0.28866666666666663, 0.0],
[0.0, 0.0, 0.0],
],
12: [
[-0.5, 0.86599999999999999, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666666666666666, 0.28866666666666663, 0.0],
],
13: [
[-1.5, 0.86599999999999999, 0.0],
[-0.5, 0.86599999999999999, 0.0],
[-0.16666666666666666, 0.28866666666666663, 0.0],
[-0.5, 0.28866666666666663, 0.0],
],
14: [
[-2.0, 0.0, 0.0],
[-1.5, 0.86599999999999999, 0.0],
[-0.5, 0.28866666666666663, 0.0],
[-0.66666666666666663, 0.0, 0.0],
],
15: [
[-1.5, -0.86599999999999999, 0.0],
[-2.0, 0.0, 0.0],
[-0.66666666666666663, 0.0, 0.0],
[-0.5, -0.28866666666666663, 0.0],
],
16: [
[-0.5, -0.86599999999999999, 0.0],
[-1.5, -0.86599999999999999, 0.0],
[-0.5, -0.28866666666666663, 0.0],
[-0.16666666666666666, -0.28866666666666663, 0.0],
],
17: [
[0.0, 0.0, 0.0],
[-0.5, -0.86599999999999999, 0.0],
[-0.16666666666666666, -0.28866666666666663, 0.0],
[0.0, 0.0, 0.0],
],
18: [
[-0.5, -0.86599999999999999, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666666666666666, -0.28866666666666663, 0.0],
],
19: [
[0.0, -1.732, 0.0],
[-0.5, -0.86599999999999999, 0.0],
[-0.16666666666666666, -0.28866666666666663, 0.0],
[0.0, -0.57733333333333325, 0.0],
],
20: [
[1.0, -1.732, 0.0],
[0.0, -1.732, 0.0],
[0.0, -0.57733333333333325, 0.0],
[0.33333333333333331, -0.57733333333333325, 0.0],
],
21: [
[1.5, -0.86599999999999999, 0.0],
[1.0, -1.732, 0.0],
[0.33333333333333331, -0.57733333333333325, 0.0],
[0.5, -0.28866666666666663, 0.0],
],
22: [
[1.0, 0.0, 0.0],
[1.5, -0.86599999999999999, 0.0],
[0.5, -0.28866666666666663, 0.0],
[0.33333333333333331, 0.0, 0.0],
],
23: [
[0.0, 0.0, 0.0],
[1.0, 0.0, 0.0],
[0.33333333333333331, 0.0, 0.0],
[0.0, 0.0, 0.0],
],
}
expected_res = pd.Series(dict_expected_res)
## test standard on a 3d-epithelium
res = eptm.face_polygons(["x", "y", "z"])
assert all([(expected_res[i] == res[i]).all()
for i in range(res.shape[0])])
def test_3faces():
datasets, specs = three_faces_sheet()
eptm = Epithelium("3faces_2D", datasets, specs)
assert (eptm.Nc, eptm.Nv, eptm.Ne) == (3, 13, 18)
def test_verts_in_face_connectivity():
data, specs = three_faces_sheet()
sheet = Sheet("test", data, specs)
vfc = connectivity.verts_in_face_connectivity(sheet)
assert vfc[0][vfc[0] == 2].shape == (3, )
class TestsPlt:
sheet = Sheet("test", *three_faces_sheet())
draw_specs = config.draw.sheet_spec()
def test_quick_edge_draw(self):
fig, ax = quick_edge_draw(self.sheet)
assert ax.lines[0].get_xydata().shape == (54, 2)
def test_sheet_view(self):
self.sheet = Sheet("test", *three_faces_sheet())
self.sheet.vert_df["rand"] = np.linspace(
0.0, 1.0, num=self.sheet.vert_df.shape[0]
)
cmap = plt.cm.get_cmap("viridis")
color_cmap = cmap(self.sheet.vert_df.rand)
self.draw_specs["vert"]["visible"] = True
self.draw_specs["vert"]["color"] = color_cmap
self.draw_specs["vert"]["alpha"] = 0.5
self.draw_specs["vert"]["s"] = 500
self.sheet.face_df["col"] = np.linspace(
0.0, 1.0, num=self.sheet.face_df.shape[0]
)
self.draw_specs["face"]["color"] = self.sheet.face_df["col"]
self.draw_specs["face"]["visible"] = True
self.draw_specs["face"]["alpha"] = 0.5
self.sheet.edge_df["rand"] = np.linspace(
0.0, 1.0, num=self.sheet.edge_df.shape[0]
)[::-1]
self.draw_specs["edge"]["visible"] = True
self.draw_specs["edge"]["color"] = self.sheet.edge_df["rand"] # [0, 0, 0, 1]
self.draw_specs["edge"]["alpha"] = 1.0
self.draw_specs["edge"]["color_range"] = 0, 3
self.draw_specs["edge"]["width"] = 1.0 * np.linspace(
0.0, 1.0, num=self.sheet.edge_df.shape[0]
)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert len(ax.collections) == 3
assert ax.collections[0].get_edgecolors().shape == (13, 4)
assert ax.collections[1].get_edgecolors().shape == (18, 4)
assert ax.collections[2].get_edgecolors().shape == (0, 4)
assert ax.collections[2].get_facecolors().shape == (3, 4)
self.draw_specs["edge"]["head_width"] = 1.0
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert len(ax.collections) == 3
assert ax.collections[0].get_edgecolors().shape == (13, 4)
assert ax.collections[1].get_edgecolors().shape == (18, 4)
assert ax.collections[2].get_edgecolors().shape == (0, 4)
assert ax.collections[2].get_facecolors().shape == (3, 4)
def test_sheet_view_color_string(self):
self.draw_specs["edge"]["color"] = "k"
self.draw_specs["face"]["color"] = "red"
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert ax.collections[1].get_edgecolors().shape == (1, 4)
assert ax.collections[2].get_facecolors().shape == (1, 4)
def test_sheet_view_color_partial_visibility(self):
self.draw_specs["face"]["color"] = np.random.rand(3, 4)
self.sheet.face_df["visible"] = False
self.sheet.face_df.loc[0, "visible"] = True
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert ax.collections[2].get_facecolors().shape == (1, 4)
def test_sheet_view_color_null_visibility(self):
self.draw_specs["face"]["color"] = np.random.rand(3, 4)
self.sheet.face_df["visible"] = False
with pytest.warns(UserWarning):
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
assert ax.collections[2].get_facecolors().shape == (3, 4)
def test_sheet_view_homogenous_color(self):
with pytest.warns(UserWarning):
self.draw_specs["face"]["color"] = np.ones(3)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
with pytest.warns(UserWarning):
self.draw_specs["edge"]["color"] = np.ones(self.sheet.Ne)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
with pytest.warns(UserWarning):
self.draw_specs["edge"]["color"] = np.ones(self.sheet.Nv)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
def test_sheet_view_invalid_color_array(self):
with pytest.raises(ValueError):
self.draw_specs["face"]["color"] = np.arange(5)
self.draw_specs["edge"]["color"] = np.arange(self.sheet.Nv)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
def test_per_vertex_edge_colors(self):
self.draw_specs["face"]["color"] = "red"
self.sheet.face_df["visible"] = True
self.draw_specs["edge"]["color"] = np.random.random(self.sheet.Nv)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
def test_sheet_view_callable(self):
with pytest.raises(ValueError):
self.draw_specs["face"]["color"] = lambda sheet: np.ones(5)
self.draw_specs["edge"]["color"] = lambda sheet: np.ones(5)
fig, ax = sheet_view(self.sheet, ["x", "y"], **self.draw_specs)
def test_triangular_mesh():
datasets, specs = three_faces_sheet()
eptm = Epithelium("3faces_2D", datasets, specs)
vertices, faces = eptm.triangular_mesh(["x", "y", "z"], False)
assert vertices.shape == (16, 3)
assert faces.shape == (18, 3)
def test_mono_update_perimeters():
datasets_2d, _ = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d, method="translation")
specs = config.geometry.bulk_spec()
eptm = Epithelium("test_volume", datasets, specs, coords=["x", "y", "z"])
def test_grow():
sheet = Sheet("emin", *three_faces_sheet())
sheet.face_df["prefered_vol"] = 1.0
grow(sheet, 0, 1.2)
assert sheet.face_df.loc[0, "prefered_vol"] == 1.2
def test_get_next():
sheet = Sheet("emin", *three_faces_sheet())
next_ = utils.get_next(sheet)
expected = np.array(
[1, 2, 3, 4, 5, 0, 7, 8, 9, 10, 11, 6, 13, 14, 15, 16, 17, 12])
np.testing.assert_array_equal(next_, expected)
def test_set_value():
sheet = Sheet("emin", *three_faces_sheet())
sheet.face_df["prefered_vol"] = 1.0
set_value(sheet, "face", 0, 12.0, "prefered_vol")
assert sheet.face_df.loc[0, "prefered_vol"] == 12.0
assert sheet.face_df.loc[1, "prefered_vol"] == 1.0
def test_decrease():
sheet = Sheet("emin", *three_faces_sheet())
sheet.face_df["prefered_vol"] = 1.0
decrease(sheet, "face", 0, 1.6, "prefered_vol")
assert sheet.face_df.loc[0, "prefered_vol"] == 0.625
from tyssue import Sheet
from tyssue.generation import three_faces_sheet
from collisions import self_intersections
sheet = Sheet("test", *three_faces_sheet())
assert len(self_intersections(sheet) == 0)
def test_monolayer_with_lamina():
sheet_dsets, _ = three_faces_sheet()
dsets = extrude(sheet_dsets, method="translation")
mono = MonolayerWithLamina("test", dsets, config.geometry.bulk_spec())
assert mono.lamina_edges.shape == (3,)
def test_bulk_update_vol():
datasets_2d, _ = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d, method="translation")
specs = config.geometry.bulk_spec()
eptm = Epithelium("test_volume", datasets, specs, coords=["x", "y", "z"])
BulkGeometry.update_all(eptm)
expected_cell_df = pd.DataFrame.from_dict({
"cell": [0, 1, 2],
"x": [0.5, -1.0, 0.5],
"y": [8.660000e-01, -6.167906e-18, -8.6600000e-01],
"z": [-0.5, -0.5, -0.5],
"is_alive": [True, True, True],
"num_faces": [8, 8, 8],
"vol": [2.598, 2.598, 2.598],
}).set_index("cell")
expected_face_centroids = pd.DataFrame.from_dict({
"face":
list(range(24)),
"x": [
0.5,
-1.0,
0.5,
0.5,
-1.0,
0.5,
0.5,
1.25,
1.25,
0.5,
-0.25,
-0.25,
-0.25,
-1.0,
-1.75,
-1.75,
-1.0,
-0.25,
-0.25,
-0.25,
0.5,
1.25,
1.25,
0.5,
],
"y": [
0.86599999999999999,
0.0,
-0.86599999999999999,
0.86599999999999999,
0.0,
-0.86599999999999999,
0.0,
0.433,
1.2989999999999999,
1.732,
1.2989999999999999,
0.433,
0.433,
0.86599999999999999,
0.433,
-0.433,
-0.86599999999999999,
-0.433,
-0.433,
-1.2989999999999999,
-1.732,
-1.2989999999999999,
-0.433,
0.0,
],
"z": [
0.0,
0.0,
0.0,
-1.0,
-1.0,
-1.0,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
-0.5,
],
}).set_index("face")
## only update class methods in BulkGeometry : update_vol, update_centroids
tolerance = 1e-16
## check volumes
assert all((expected_cell_df["vol"] - eptm.cell_df["vol"])**2 < tolerance)
## check centroids
assert all((expected_face_centroids -
eptm.face_df.loc[:, ["x", "y", "z"]])**2 < tolerance)
def test_idx_lookup():
datasets, specs = three_faces_sheet()
eptm = Epithelium("3faces_2D", datasets, specs)
eptm.face_df["id"] = eptm.face_df.index.values
assert eptm.idx_lookup(1, "face") == 1
def test_cut_out():
datasets_2d, _ = three_faces_sheet()
datasets = extrude(datasets_2d, method="translation")
eptm = Epithelium("3faces_3D", datasets)
bounding_box_xy = np.array([[-1.0, 10.0], [-1.5, 1.5]])
bounding_box_yx = np.array([[-1.5, 1.5], [-1.0, 10.0]])
bounding_box_xyz = np.array([[-10.0, 10.0], [-1.5, 10.0], [-2.0, 1.0]])
expected_index_xy = pd.Index(
[
2,
3,
4,
7,
8,
9,
10,
13,
14,
15,
20,
21,
22,
25,
26,
27,
28,
31,
32,
33,
44,
46,
47,
48,
49,
50,
51,
52,
53,
54,
64,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77,
78,
88,
90,
91,
92,
93,
94,
95,
96,
97,
98,
],
name="edge",
dtype="int64",
)
expected_index_xyz = pd.Index(
[13, 14, 15, 31, 32, 33, 88, 90, 91, 92, 93, 94, 95, 96, 97, 98],
name="edge",
dtype="int64",
)
# test 2-coords, ordered
res = eptm.cut_out(bbox=bounding_box_xy, coords=["x", "y"])
assert len(res) == len(expected_index_xy)
assert (res == expected_index_xy).all()
# test 2-coords, inverse order
res = eptm.cut_out(bbox=bounding_box_yx, coords=["y", "x"])
assert len(res) == len(expected_index_xy)
assert (res == expected_index_xy).all()
# test 3-coords
res = eptm.cut_out(bbox=bounding_box_xyz, coords=["x", "y", "z"])
assert len(res) == len(expected_index_xyz)
assert (res == expected_index_xyz).all()
# test default coords argument
res = eptm.cut_out(bbox=bounding_box_xy)
assert len(res) == len(expected_index_xy)
assert (res == expected_index_xy).all()
def test_summation():
datasets_2d, specs = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d)
eptm = Epithelium("3faces_3D", datasets, specs)
data = eptm.edge_df.index.values
assert_array_equal(
eptm.sum_cell(data).values.flatten(), np.array([1278, 1926, 2574]))
sum_trgt = np.array([
462,
302,
88,
97,
106,
248,
142,
151,
160,
356,
196,
205,
214,
501,
340,
107,
116,
125,
286,
161,
170,
179,
394,
215,
224,
233,
])
assert_array_equal(eptm.sum_trgt(data).values.flatten(), sum_trgt)
sum_srce = np.array([
441,
300,
87,
96,
105,
246,
141,
150,
159,
354,
195,
204,
213,
522,
342,
108,
117,
126,
288,
162,
171,
180,
396,
216,
225,
234,
])
assert_array_equal(eptm.sum_srce(data).values.flatten(), sum_srce)
sum_face = np.array([
15,
51,
87,
123,
159,
195,
150,
166,
182,
198,
214,
230,
246,
262,
278,
294,
310,
326,
342,
358,
374,
390,
406,
422,
])
assert_array_equal(eptm.sum_face(data).values.flatten(), sum_face)
def test_extrude_invalid_method():
datasets, specs = generation.three_faces_sheet()
with raises(ValueError):
datasets_3d = extrude(datasets, method="invalid_method")
def test_remove():
datasets, specs = three_faces_sheet()
datasets = extrude(datasets, method="translation")
eptm = Epithelium("3Faces_3D", datasets, specs)
dict_after = {
"srce": {
0: 0,
1: 2,
2: 3,
3: 4,
4: 5,
5: 6,
6: 0,
7: 6,
8: 7,
9: 8,
10: 9,
11: 1,
12: 12,
13: 13,
14: 14,
15: 15,
16: 16,
17: 10,
18: 16,
19: 17,
20: 18,
21: 19,
22: 11,
23: 10,
24: 2,
25: 0,
26: 10,
27: 12,
28: 3,
29: 2,
30: 12,
31: 13,
32: 4,
33: 3,
34: 13,
35: 14,
36: 5,
37: 4,
38: 14,
39: 15,
40: 6,
41: 5,
42: 15,
43: 16,
44: 0,
45: 6,
46: 16,
47: 10,
48: 6,
49: 0,
50: 10,
51: 16,
52: 7,
53: 6,
54: 16,
55: 17,
56: 8,
57: 7,
58: 17,
59: 18,
60: 9,
61: 8,
62: 18,
63: 19,
64: 1,
65: 9,
66: 19,
67: 11,
68: 0,
69: 1,
70: 11,
71: 10,
},
"trgt": {
0: 2,
1: 3,
2: 4,
3: 5,
4: 6,
5: 0,
6: 6,
7: 7,
8: 8,
9: 9,
10: 1,
11: 0,
12: 10,
13: 12,
14: 13,
15: 14,
16: 15,
17: 16,
18: 10,
19: 16,
20: 17,
21: 18,
22: 19,
23: 11,
24: 0,
25: 10,
26: 12,
27: 2,
28: 2,
29: 12,
30: 13,
31: 3,
32: 3,
33: 13,
34: 14,
35: 4,
36: 4,
37: 14,
38: 15,
39: 5,
40: 5,
41: 15,
42: 16,
43: 6,
44: 6,
45: 16,
46: 10,
47: 0,
48: 0,
49: 10,
50: 16,
51: 6,
52: 6,
53: 16,
54: 17,
55: 7,
56: 7,
57: 17,
58: 18,
59: 8,
60: 8,
61: 18,
62: 19,
63: 9,
64: 9,
65: 19,
66: 11,
67: 1,
68: 1,
69: 11,
70: 10,
71: 0,
},
"face": {
0: 0,
1: 0,
2: 0,
3: 0,
4: 0,
5: 0,
6: 1,
7: 1,
8: 1,
9: 1,
10: 1,
11: 1,
12: 2,
13: 2,
14: 2,
15: 2,
16: 2,
17: 2,
18: 3,
19: 3,
20: 3,
21: 3,
22: 3,
23: 3,
24: 4,
25: 4,
26: 4,
27: 4,
28: 5,
29: 5,
30: 5,
31: 5,
32: 6,
33: 6,
34: 6,
35: 6,
36: 7,
37: 7,
38: 7,
39: 7,
40: 8,
41: 8,
42: 8,
43: 8,
44: 9,
45: 9,
46: 9,
47: 9,
48: 10,
49: 10,
50: 10,
51: 10,
52: 11,
53: 11,
54: 11,
55: 11,
56: 12,
57: 12,
58: 12,
59: 12,
60: 13,
61: 13,
62: 13,
63: 13,
64: 14,
65: 14,
66: 14,
67: 14,
68: 15,
69: 15,
70: 15,
71: 15,
},
}
sft_after = pd.DataFrame.from_dict(dict_after)
eptm.remove([0])
assert eptm.edge_df[["srce", "trgt",
"face"]].equals(sft_after[["srce", "trgt", "face"]])
def test_retrieve_coords():
sheet = Sheet("3", *three_faces_sheet())
history = History(sheet)
history.record()
assert history.retrieve(0).coords == sheet.coords
def test_3faces():
datasets, _ = generation.three_faces_sheet()
assert datasets["edge"].shape[0] == 18
assert datasets["face"].shape[0] == 3
assert datasets["vert"].shape[0] == 13
def test_polygons():
datasets_2d, specs = three_faces_sheet(zaxis=True)
datasets = extrude(datasets_2d, scale=1 / 3.0)
eptm = Epithelium("3faces_3D", datasets, specs)
RNRGeometry.update_all(eptm)
with raises(ValueError):
fp = eptm.face_polygons()
eptm.reset_index(order=True)
expected_res = [
[
[0.0, 0.0, 0.0],
[1.0, 0.0, 0.0],
[1.5, 0.866, 0.0],
[1.0, 1.732, 0.0],
[0.0, 1.732, 0.0],
[-0.5, 0.866, 0.0],
],
[
[-1.5, -0.866, 0.0],
[-0.5, -0.866, 0.0],
[0.0, 0.0, 0.0],
[-0.5, 0.866, 0.0],
[-1.5, 0.866, 0.0],
[-2.0, 0.0, 0.0],
],
[
[0.0, -1.732, 0.0],
[1.0, -1.732, 0.0],
[1.5, -0.866, 0.0],
[1.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.5, -0.866, 0.0],
],
[
[0.0, 0.0, 0.0],
[0.33333333, 0.0, 0.0],
[0.5, 0.28866667, 0.0],
[0.33333333, 0.57733333, 0.0],
[0.0, 0.57733333, 0.0],
[-0.16666667, 0.28866667, 0.0],
],
[
[-0.5, -0.28866667, 0.0],
[-0.16666667, -0.28866667, 0.0],
[0.0, 0.0, 0.0],
[-0.16666667, 0.28866667, 0.0],
[-0.5, 0.28866667, 0.0],
[-0.66666667, 0.0, 0.0],
],
[
[0.0, -0.57733333, 0.0],
[0.33333333, -0.57733333, 0.0],
[0.5, -0.28866667, 0.0],
[0.33333333, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666667, -0.28866667, 0.0],
],
[[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.33333333, 0.0, 0.0]],
[
[0.5, 0.28866667, 0.0],
[0.33333333, 0.0, 0.0],
[1.0, 0.0, 0.0],
[1.5, 0.866, 0.0],
],
[
[0.33333333, 0.57733333, 0.0],
[0.5, 0.28866667, 0.0],
[1.5, 0.866, 0.0],
[1.0, 1.732, 0.0],
],
[
[0.0, 0.57733333, 0.0],
[0.33333333, 0.57733333, 0.0],
[1.0, 1.732, 0.0],
[0.0, 1.732, 0.0],
],
[
[-0.5, 0.866, 0.0],
[-0.16666667, 0.28866667, 0.0],
[0.0, 0.57733333, 0.0],
[0.0, 1.732, 0.0],
],
[
[0.0, 0.0, 0.0],
[-0.16666667, 0.28866667, 0.0],
[0.0, 0.0, 0.0],
[-0.5, 0.866, 0.0],
],
[
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666667, 0.28866667, 0.0],
[-0.5, 0.866, 0.0],
],
[
[-0.5, 0.28866667, 0.0],
[-0.16666667, 0.28866667, 0.0],
[-0.5, 0.866, 0.0],
[-1.5, 0.866, 0.0],
],
[
[-2.0, 0.0, 0.0],
[-0.66666667, 0.0, 0.0],
[-0.5, 0.28866667, 0.0],
[-1.5, 0.866, 0.0],
],
[
[-1.5, -0.866, 0.0],
[-0.5, -0.28866667, 0.0],
[-0.66666667, 0.0, 0.0],
[-2.0, 0.0, 0.0],
],
[
[-1.5, -0.866, 0.0],
[-0.5, -0.866, 0.0],
[-0.16666667, -0.28866667, 0.0],
[-0.5, -0.28866667, 0.0],
],
[
[-0.5, -0.866, 0.0],
[0.0, 0.0, 0.0],
[-0.16666667, -0.28866667, 0.0],
[0.0, 0.0, 0.0],
],
[
[-0.5, -0.866, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[-0.16666667, -0.28866667, 0.0],
],
[
[0.0, -1.732, 0.0],
[0.0, -0.57733333, 0.0],
[-0.16666667, -0.28866667, 0.0],
[-0.5, -0.866, 0.0],
],
[
[0.0, -1.732, 0.0],
[1.0, -1.732, 0.0],
[0.33333333, -0.57733333, 0.0],
[0.0, -0.57733333, 0.0],
],
[
[1.0, -1.732, 0.0],
[1.5, -0.866, 0.0],
[0.5, -0.28866667, 0.0],
[0.33333333, -0.57733333, 0.0],
],
[
[1.5, -0.866, 0.0],
[1.0, 0.0, 0.0],
[0.33333333, 0.0, 0.0],
[0.5, -0.28866667, 0.0],
],
[[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.33333333, 0.0, 0.0],
[0.0, 0.0, 0.0]],
]
expected_res = [np.array(poly) for poly in expected_res]
res = eptm.face_polygons(["x", "y", "z"])
for i in range(res.shape[0]):
np.testing.assert_almost_equal(expected_res[i], res[i], decimal=4)
def test_srce_trgt_connectivity():
data, specs = three_faces_sheet()
sheet = Sheet("test", data, specs)
stc = connectivity.srce_trgt_connectivity(sheet)
expected = np.array([3, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1])
np.testing.assert_array_equal(stc.sum(axis=0), expected)
def test_remove():
datasets, specs = three_faces_sheet()
datasets = extrude(datasets, method="translation")
eptm = Epithelium("3Faces_3D", datasets, specs)
dict_before = {
"srce": {
0: 0,
1: 1,
2: 2,
3: 3,
4: 4,
5: 5,
6: 0,
7: 5,
8: 6,
9: 7,
10: 8,
11: 9,
12: 0,
13: 9,
14: 10,
15: 11,
16: 12,
17: 1,
18: 14,
19: 15,
20: 16,
21: 17,
22: 18,
23: 13,
24: 18,
25: 19,
26: 20,
27: 21,
28: 22,
29: 13,
30: 22,
31: 23,
32: 24,
33: 25,
34: 14,
35: 13,
36: 1,
37: 0,
38: 13,
39: 14,
40: 2,
41: 1,
42: 14,
43: 15,
44: 3,
45: 2,
46: 15,
47: 16,
48: 4,
49: 3,
50: 16,
51: 17,
52: 5,
53: 4,
54: 17,
55: 18,
56: 0,
57: 5,
58: 18,
59: 13,
60: 5,
61: 0,
62: 13,
63: 18,
64: 6,
65: 5,
66: 18,
67: 19,
68: 7,
69: 6,
70: 19,
71: 20,
72: 8,
73: 7,
74: 20,
75: 21,
76: 9,
77: 8,
78: 21,
79: 22,
80: 0,
81: 9,
82: 22,
83: 13,
84: 9,
85: 0,
86: 13,
87: 22,
88: 10,
89: 9,
90: 22,
91: 23,
92: 11,
93: 10,
94: 23,
95: 24,
96: 12,
97: 11,
98: 24,
99: 25,
100: 1,
101: 12,
102: 25,
103: 14,
104: 0,
105: 1,
106: 14,
107: 13,
},
"trgt": {
0: 1,
1: 2,
2: 3,
3: 4,
4: 5,
5: 0,
6: 5,
7: 6,
8: 7,
9: 8,
10: 9,
11: 0,
12: 9,
13: 10,
14: 11,
15: 12,
16: 1,
17: 0,
18: 13,
19: 14,
20: 15,
21: 16,
22: 17,
23: 18,
24: 13,
25: 18,
26: 19,
27: 20,
28: 21,
29: 22,
30: 13,
31: 22,
32: 23,
33: 24,
34: 25,
35: 14,
36: 0,
37: 13,
38: 14,
39: 1,
40: 1,
41: 14,
42: 15,
43: 2,
44: 2,
45: 15,
46: 16,
47: 3,
48: 3,
49: 16,
50: 17,
51: 4,
52: 4,
53: 17,
54: 18,
55: 5,
56: 5,
57: 18,
58: 13,
59: 0,
60: 0,
61: 13,
62: 18,
63: 5,
64: 5,
65: 18,
66: 19,
67: 6,
68: 6,
69: 19,
70: 20,
71: 7,
72: 7,
73: 20,
74: 21,
75: 8,
76: 8,
77: 21,
78: 22,
79: 9,
80: 9,
81: 22,
82: 13,
83: 0,
84: 0,
85: 13,
86: 22,
87: 9,
88: 9,
89: 22,
90: 23,
91: 10,
92: 10,
93: 23,
94: 24,
95: 11,
96: 11,
97: 24,
98: 25,
99: 12,
100: 12,
101: 25,
102: 14,
103: 1,
104: 1,
105: 14,
106: 13,
107: 0,
},
"face": {
0: 0,
1: 0,
2: 0,
3: 0,
4: 0,
5: 0,
6: 1,
7: 1,
8: 1,
9: 1,
10: 1,
11: 1,
12: 2,
13: 2,
14: 2,
15: 2,
16: 2,
17: 2,
18: 3,
19: 3,
20: 3,
21: 3,
22: 3,
23: 3,
24: 4,
25: 4,
26: 4,
27: 4,
28: 4,
29: 4,
30: 5,
31: 5,
32: 5,
33: 5,
34: 5,
35: 5,
36: 6,
37: 6,
38: 6,
39: 6,
40: 7,
41: 7,
42: 7,
43: 7,
44: 8,
45: 8,
46: 8,
47: 8,
48: 9,
49: 9,
50: 9,
51: 9,
52: 10,
53: 10,
54: 10,
55: 10,
56: 11,
57: 11,
58: 11,
59: 11,
60: 12,
61: 12,
62: 12,
63: 12,
64: 13,
65: 13,
66: 13,
67: 13,
68: 14,
69: 14,
70: 14,
71: 14,
72: 15,
73: 15,
74: 15,
75: 15,
76: 16,
77: 16,
78: 16,
79: 16,
80: 17,
81: 17,
82: 17,
83: 17,
84: 18,
85: 18,
86: 18,
87: 18,
88: 19,
89: 19,
90: 19,
91: 19,
92: 20,
93: 20,
94: 20,
95: 20,
96: 21,
97: 21,
98: 21,
99: 21,
100: 22,
101: 22,
102: 22,
103: 22,
104: 23,
105: 23,
106: 23,
107: 23,
},
}
dict_after = {
"srce": {
0: 0,
1: 2,
2: 3,
3: 4,
4: 5,
5: 6,
6: 0,
7: 6,
8: 7,
9: 8,
10: 9,
11: 1,
12: 12,
13: 13,
14: 14,
15: 15,
16: 16,
17: 10,
18: 16,
19: 17,
20: 18,
21: 19,
22: 11,
23: 10,
24: 2,
25: 0,
26: 10,
27: 12,
28: 3,
29: 2,
30: 12,
31: 13,
32: 4,
33: 3,
34: 13,
35: 14,
36: 5,
37: 4,
38: 14,
39: 15,
40: 6,
41: 5,
42: 15,
43: 16,
44: 0,
45: 6,
46: 16,
47: 10,
48: 6,
49: 0,
50: 10,
51: 16,
52: 7,
53: 6,
54: 16,
55: 17,
56: 8,
57: 7,
58: 17,
59: 18,
60: 9,
61: 8,
62: 18,
63: 19,
64: 1,
65: 9,
66: 19,
67: 11,
68: 0,
69: 1,
70: 11,
71: 10,
},
"trgt": {
0: 2,
1: 3,
2: 4,
3: 5,
4: 6,
5: 0,
6: 6,
7: 7,
8: 8,
9: 9,
10: 1,
11: 0,
12: 10,
13: 12,
14: 13,
15: 14,
16: 15,
17: 16,
18: 10,
19: 16,
20: 17,
21: 18,
22: 19,
23: 11,
24: 0,
25: 10,
26: 12,
27: 2,
28: 2,
29: 12,
30: 13,
31: 3,
32: 3,
33: 13,
34: 14,
35: 4,
36: 4,
37: 14,
38: 15,
39: 5,
40: 5,
41: 15,
42: 16,
43: 6,
44: 6,
45: 16,
46: 10,
47: 0,
48: 0,
49: 10,
50: 16,
51: 6,
52: 6,
53: 16,
54: 17,
55: 7,
56: 7,
57: 17,
58: 18,
59: 8,
60: 8,
61: 18,
62: 19,
63: 9,
64: 9,
65: 19,
66: 11,
67: 1,
68: 1,
69: 11,
70: 10,
71: 0,
},
"face": {
0: 0,
1: 0,
2: 0,
3: 0,
4: 0,
5: 0,
6: 1,
7: 1,
8: 1,
9: 1,
10: 1,
11: 1,
12: 2,
13: 2,
14: 2,
15: 2,
16: 2,
17: 2,
18: 3,
19: 3,
20: 3,
21: 3,
22: 3,
23: 3,
24: 4,
25: 4,
26: 4,
27: 4,
28: 5,
29: 5,
30: 5,
31: 5,
32: 6,
33: 6,
34: 6,
35: 6,
36: 7,
37: 7,
38: 7,
39: 7,
40: 8,
41: 8,
42: 8,
43: 8,
44: 9,
45: 9,
46: 9,
47: 9,
48: 10,
49: 10,
50: 10,
51: 10,
52: 11,
53: 11,
54: 11,
55: 11,
56: 12,
57: 12,
58: 12,
59: 12,
60: 13,
61: 13,
62: 13,
63: 13,
64: 14,
65: 14,
66: 14,
67: 14,
68: 15,
69: 15,
70: 15,
71: 15,
},
}
sft_before = pd.DataFrame.from_dict(dict_before)
sft_after = pd.DataFrame.from_dict(dict_after)
eptm.remove([0])
assert eptm.edge_df[["srce", "trgt",
"face"]].equals(sft_after[["srce", "trgt", "face"]])
def test_ef_connect():
data, specs = three_faces_sheet()
sheet = Sheet("test", data, specs)
ef_connect = connectivity.edge_in_face_connectivity(sheet)
idx = sheet.edge_df.query(f"face == {sheet.Nf-1}").index
assert ef_connect[idx[0], idx[1]]
def test_wrong_datasets_keys():
datasets, specs = three_faces_sheet()
datasets["edges"] = datasets["edge"]
del datasets["edge"]
with raises(ValueError):
eptm = Epithelium("3faces_2D", datasets, specs)
def test_warning():
sheet = Sheet("3", *three_faces_sheet())
with pytest.warns(UserWarning):
history = History(sheet, extra_cols={"vert": ["invalid_column"]})
def test_shrink():
sheet = Sheet("emin", *three_faces_sheet())
sheet.face_df["prefered_vol"] = 1.0
shrink(sheet, 0, 0.6)
assert sheet.face_df.loc[0, "prefered_vol"] == 0.625