def test_distance():
exp_organo = generate_ring(3, 1, 2)
th_organo = generate_ring(3, 1, 2)
exp_organo.vert_df.loc[0, 'x'] += 1
distance = _distance(exp_organo, th_organo)
assert np.all(
np.equal(distance, np.concatenate(([1], np.zeros(exp_organo.Nv - 1)))))
def test_distance_regularized():
exp_organo = generate_ring(3, 1, 2)
th_organo = generate_ring(3, 1, 2)
geom.update_all(exp_organo)
geom.update_all(th_organo)
specs = {
'face': {
'is_alive': 1,
'prefered_area': 1.1 * th_organo.face_df.area,
'area_elasticity': 1,
},
'edge': {
'ux': 0.,
'uy': 0.,
'uz': 0.,
'line_tension': 0.01,
'is_active': 1
},
'vert': {
'adhesion_strength': 0.,
'x_ecm': 0.,
'y_ecm': 0.,
'is_active': 1
},
'settings': {
'lumen_elasticity': 0.01,
'lumen_prefered_vol': th_organo.settings['lumen_volume'],
'lumen_volume': th_organo.settings['lumen_volume']
}
}
exp_organo.update_specs(specs, reset=True)
th_organo.update_specs(specs, reset=True)
param_tension_only = {('edge', 'line_tension'): np.ones(12)}
param_with_lumen = {
('edge', 'line_tension'): np.ones(12),
('lumen_prefered_vol', None): th_organo.settings['lumen_volume']
}
for basal_reg, apical_reg in ((0, 0), (0, 1), (1, 0), (1, 1)):
for variables in (param_with_lumen, param_tension_only):
to_regularize = {'dic': {'apical': basal_reg, 'basal': apical_reg}}
reg_weight = 0.01
energy_opt = {'options': {'gtol': 1e-1, 'ftol': 1e-1}}
exp_organo.vert_df.loc[0, 'x'] += 1
res = distance_regularized(exp_organo, th_organo, variables,
Solver, geom, model, **energy_opt)
assert isinstance(res, np.ndarray)
assert res.all() >= 0
assert res.any() > 0
def _create_org():
organo = generate_ring(3, 1, 2)
geom.update_all(organo)
alpha = 1 + 1 / (20 * (organo.settings['R_out'] - organo.settings['R_in']))
specs = {
'face': {
'is_alive': 1,
'prefered_area': list(alpha * organo.face_df.area.values),
'area_elasticity': 1.,
},
'edge': {
'ux': 0.,
'uy': 0.,
'uz': 0.,
'line_tension': 0.1,
'is_active': 1
},
'vert': {
'adhesion_strength': 0.,
'x_ecm': 0.,
'y_ecm': 0.,
'is_active': 1
},
'settings': {
'lumen_elasticity': 0.1,
'lumen_prefered_vol': organo.settings['lumen_volume'],
'lumen_volume': organo.settings['lumen_volume']
}
}
organo.update_specs(specs, reset=True)
geom.update_all(organo)
return organo
def test_infer_pol():
organo = generate_ring(3, 1, 2)
pol_organo = organo.copy()
pol_organo.vert_df.loc[pol_organo.basal_verts, ('x', 'y')] *= 1.1
geom.update_all(pol_organo)
for val in _infer_pol(pol_organo):
assert round(val, 9) == 0.9
def test_tension_bounds():
organo = generate_ring(3, 1, 2)
organo.edge_df.loc[:, 'line_tension'] = np.ones(12)
organo.edge_df.loc[(0, 1), 'line_tension'] = [-1, 2 * 1e3]
penalties = _tension_bounds(organo)
assert len(penalties) == 3 * organo.Nf
assert penalties[0] == 1e3
assert penalties[1] == 0
assert np.argwhere(penalties != 0).squeeze() == np.array(0)
def test_right_side():
organo = generate_ring(3, 1, 2)
pol_organo = organo.copy()
pol_organo.vert_df.loc[pol_organo.basal_verts, ('x', 'y')] *= 1.1
geom.update_all(pol_organo)
cst = _right_side(pol_organo)
assert isinstance(cst, np.ndarray)
assert np.array_equal(cst.shape, (15, ))
assert np.array_equal(cst[:12], np.zeros(12))
assert not np.isnan(cst[12:]).any()
def test_t_per_cell_coefs():
organo = generate_ring(3, 1, 2)
t_per_cell = _t_per_cell_coefs(organo, _get_sim_param(3, 1, 2),
_infer_pol(organo))
assert isinstance(t_per_cell, np.ndarray)
assert np.array_equal(t_per_cell.shape, (3, 13))
assert np.array_equal(t_per_cell[:, :3], np.eye(3))
assert np.array_equal(t_per_cell[:, 3:6], np.eye(3))
assert np.array_equal(
t_per_cell[:, 6:9],
np.roll(np.eye(3) + np.roll(np.eye(3), 1, axis=0), 1, axis=1))
assert np.array_equal(t_per_cell[:, 9:], np.zeros((3, 4)))
def mesh_from_data(centers, inner_contour, outer_contour):
"""Creates an annular organoid from image data
"""
Nf = centers.shape[0]
print(tmp_eptm.datasets[elem][columns], values)
# Organize centers clockwize
origin = centers.mean(axis=1)
shifted_centers = centers - origin[np.newaxis, :]
thetas = np.arctan2(shifted_centers[:, 1], shifted_centers[:, 0])
centers = centers.take(np.argsort(thetas))
inner_vs, outer_vs = get_bissecting_vertices(centers, inner_contour,
outer_contour)
R_in = np.linalg.norm(inner_vs - inner_vs.mean(axis=1), axis=0).mean()
R_out = np.linalg.norm(outer_vs - outer_vs.mean(axis=1), axis=0).mean()
organo = generate_ring(Nf, R_in, R_out)
organo.vert_df.loc[organo.apical_verts, organo.coords] = inner_vs[::-1]
organo.vert_df.loc[organo.basal_verts, organo.coords] = outer_vs[::-1]
AnnularGeometry.update_all(organo)
specs = {
'face': {
'is_alive': 1,
'prefered_area': organo.face_df.area.mean(),
'area_elasticity': 1,
},
'edge': {
'ux': 0.,
'uy': 0.,
'fx': 0.,
'fy': 0.,
'sx': 0., # source and target coordinates
'sy': 0.,
'tx': 0.,
'ty': 0.,
'line_tension': 1e-3,
'is_active': 1
},
'vert': {
'is_active': 1
},
'settings': {
'lumen_elasticity': 10,
'lumen_prefered_vol': organo.settings['lumen_volume'],
'lumen_volume': organo.settings['lumen_volume']
}
}
organo.update_specs(specs, reset=True)
return organo
def test_prepare_tensions():
organo = generate_ring(3, 1, 2)
organo.edge_df.loc[:, 'line_tension'] = np.ones(12)
tension_array = organo.edge_df.loc[:, 'line_tension'][:3 * organo.Nf]
tension_array[0] += 1
tension_array[3 * organo.Nf - 1] += 1
tensions = prepare_tensions(organo, tension_array)
assert len(tensions) == 4 * organo.Nf
assert np.all(
np.equal(tensions[:3 * organo.Nf], tension_array[:3 * organo.Nf]))
assert np.all(
np.equal(np.roll(tensions[3 * organo.Nf:], 1),
tension_array[2 * organo.Nf:]))
def create_organo(nb_cells, r_in, r_out, seed=None, rot=None, geom=geom):
organo = generate_ring(nb_cells, r_in, r_out)
Nf = organo.Nf
geom.update_all(organo)
alpha = 1 + 1 / (20 * (organo.settings['R_out'] - organo.settings['R_in']))
specs = {
'face': {
'is_alive': 1,
'prefered_area': organo.face_df.area,
'area_elasticity': 1.,
},
'edge': {
'ux': 0.,
'uy': 0.,
'uz': 0.,
'line_tension': 0.1,
'is_active': 1
},
'vert': {
'adhesion_strength': 0.01,
'x_ecm': 0.,
'y_ecm': 0.,
'is_active': 1
},
'settings': {
'lumen_elasticity': 1.,
'lumen_prefered_vol': organo.settings['lumen_volume'],
'lumen_volume': organo.settings['lumen_volume']
}
}
organo.update_specs(specs, reset=True)
normalize_scale(organo, geom, refer='edges')
geom.update_all(organo)
if seed is not None:
symetric_tensions = set_init_point(organo.settings['R_in'],
organo.settings['R_out'], organo.Nf,
alpha)
sin_mul = 1 + (np.sin(
np.linspace(0, 2 * np.pi, organo.Nf, endpoint=False)))**2
organo.face_df.prefered_area *= np.random.normal(1.0, 0.05, organo.Nf)
organo.edge_df.line_tension = prepare_tensions(organo,
symetric_tensions)
organo.edge_df.loc[:Nf - 1,
'line_tension'] *= sin_mul * np.random.normal(
1.0, 0.05, organo.Nf)
geom.update_all(organo)
if rot is not None:
organo.vert_df.loc[:, 'x'] = (organo.vert_df.x.copy() * np.cos(rot) -
organo.vert_df.y.copy() * np.sin(rot))
print(
'rotated x',
organo.vert_df.x.copy() * np.cos(rot) -
organo.vert_df.y.copy() * np.sin(rot))
organo.vert_df.loc[:, 'y'] = (organo.vert_df.x.copy() * np.sin(rot) +
organo.vert_df.y.copy() * np.cos(rot))
print(
'rotated y',
organo.vert_df.x.copy() * np.sin(rot) +
organo.vert_df.y.copy() * np.cos(rot))
geom.update_all(organo)
organo.vert_df[['x_ecm', 'y_ecm']] = organo.vert_df[['x', 'y']]
organo.vert_df.loc[organo.basal_verts, 'adhesion_strength'] = 0.01
new_tensions = organo.edge_df.line_tension
organo.edge_df.loc[:, 'line_tension'] = new_tensions
return organo
def generate_ring_from_image(
brightfield_path,
dapi_path,
scp_model_path=None,
threshold=28,
blur=9,
rol_window_inside=100,
rol_window_outside=20,
):
"""Create an organo mesh of class AnnularSheet from a brightfield image
and a CellProfiler DAPI analysis csv file
Parameters
----------
brightfield_path : string
path to the brightfield image
dapi_path : string
path to the DAPI image
scp_model_path : string
path to the stardist model
threshold: int >=0
threshold to apply to the brightfield image
blur: int >=0
gaussian blur to apply to the brightfield image
rol_window_inside: int > 0.
Length of the window of the rolling mean on apical contour.
rol_window_outside: int > 0.
Length of the window of the rolling mean on basal contour.
Return
----------
organo : object of class AnnularSheet
the organo mesh extracted from the data
"""
membrane_dic = extract_membranes(brightfield_path, threshold, blur)
clockwise_centers = _star_convex_polynoms(dapi_path, membrane_dic,
scp_model_path)
inside_df = pd.DataFrame(membrane_dic["inside"], index=None)
outside_df = pd.DataFrame(membrane_dic["outside"], index=None)
inners = inside_df.rolling(rol_window_inside, min_periods=1).mean().values
outers = outside_df.rolling(rol_window_outside,
min_periods=1).mean().values
nb_cells = len(clockwise_centers)
org_center = membrane_dic["center_inside"] - np.full(
2, membrane_dic["img_shape"][0] / 2.0)
inner_vs, outer_vs = get_bissecting_vertices(clockwise_centers, inners,
outers, org_center)
organo = generate_ring(nb_cells, membrane_dic["rIn"], membrane_dic["rOut"])
organo.vert_df.loc[organo.apical_verts, organo.coords] = (
inner_vs[::-1] - np.full(inner_vs.shape, org_center)) * 0.323
organo.vert_df.loc[organo.basal_verts, organo.coords] = (
outer_vs[::-1] - np.full(outer_vs.shape, org_center)) * 0.323
inners = (inners - np.full(inners.shape, org_center)) * 0.323
outers = (outers - np.full(outers.shape, org_center)) * 0.323
clockwise_centers = np.array(clockwise_centers)
clockwise_centers -= np.full(outer_vs.shape, org_center)
clockwise_centers *= 0.323
organo.settings["R_in"] *= 0.323
organo.settings["R_out"] *= 0.323
return organo, inners, outers, clockwise_centers
