def test_produce_cytokines_n(
macrophage_list: MacrophageCellList,
grid: RectangularGrid,
populated_fungus: FungusCellList,
cyto,
):
m_n = 10
macrophage_list.append(
MacrophageCellData.create_cell(point=Point(x=grid.x[3],
y=grid.y[3],
z=grid.z[3]), ))
vox = grid.get_voxel(macrophage_list[0]['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
for cell in populated_fungus.cell_data:
vox = grid.get_voxel(cell['point'])
assert vox.z in [1, 2, 3, 4, 5] and vox.y in [1, 2, 3, 4, 5] and vox.x in [
1, 2, 3, 4, 5
]
# 1
m_det = 1
assert cyto[3, 3, 3] == 0
macrophage_list.produce_cytokines(m_det, m_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 30
# 2
m_det = 2
cyto[3, 3, 3] = 0
macrophage_list.produce_cytokines(m_det, m_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 50
def test_internalize_conidia_0(macrophage_list: MacrophageCellList,
grid: RectangularGrid,
fungus_list: FungusCellList):
m_det = 0
point = Point(x=35, y=35, z=35)
macrophage_list.append(MacrophageCellData.create_cell(point=point))
fungus_list.append(
FungusCellData.create_cell(point=point,
status=FungusCellData.Status.RESTING))
vox = grid.get_voxel(macrophage_list[0]['point'])
assert len(fungus_list.get_cells_in_voxel(vox)) == 1
f_index = fungus_list.get_cells_in_voxel(vox) # 0
assert f_index == 0
fungus_list[f_index]['form'] = FungusCellData.Form.CONIDIA
fungus_list[f_index]['status'] = FungusCellData.Status.RESTING
macrophage_list.internalize_conidia(m_det, 50, 1, grid, fungus_list)
assert grid.get_voxel(fungus_list[f_index]['point']) == vox
assert fungus_list.cell_data['internalized'][f_index]
assert macrophage_list.len_phagosome(0) == 1
def test_produce_cytokines_n(
neutrophil_list: NeutrophilCellList,
grid: RectangularGrid,
populated_fungus: FungusCellList,
cyto,
):
n_n = 10
neutrophil_list.append(
NeutrophilCellData.create_cell(
point=Point(x=grid.x[3], y=grid.y[3], z=grid.z[3]),
status=NeutrophilCellData.Status.NONGRANULATING,
granule_count=5,
)
)
vox = grid.get_voxel(neutrophil_list[0]['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
for cell in populated_fungus.cell_data:
vox = grid.get_voxel(cell['point'])
assert vox.z in [1, 2, 3, 4, 5] and vox.y in [1, 2, 3, 4, 5] and vox.x in [1, 2, 3, 4, 5]
# 1
n_det = 1
assert cyto[3, 3, 3] == 0
neutrophil_list.produce_cytokines(n_det, n_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 30
# 2
n_det = 2
cyto[3, 3, 3] = 0
neutrophil_list.produce_cytokines(n_det, n_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 50
def periodic_discrete_laplacian(
grid: RectangularGrid,
mask: np.ndarray,
dtype: np.dtype = _dtype_float64) -> csr_matrix:
"""Return a laplacian operator with periodic boundary conditions.
This computes a standard laplacian operator as a scipy linear operator, except it is
restricted to a grid mask. The use case for this is to compute surface diffusion
on a gridded variable. The mask is generated from a category on the lung_tissue
variable.
"""
graph_shape = len(grid), len(grid)
z_extent, y_extent, x_extent = grid.shape
laplacian = dok_matrix(graph_shape, dtype=dtype)
delta_z = grid.delta(0)
delta_y = grid.delta(1)
delta_x = grid.delta(2)
for k, j, i in zip(*(mask).nonzero()):
voxel = Voxel(x=i, y=j, z=k)
voxel_index = grid.get_flattened_index(voxel)
for offset in [(-1, 0, 0), (1, 0, 0), (0, -1, 0), (0, 1, 0),
(0, 0, -1), (0, 0, 1)]:
# voxel coordinate displacements
dk, dj, di = offset
# find the neighbor for periodic boundary conditions
neighbor: Voxel = Voxel(x=(i + di) % x_extent,
y=(j + dj) % y_extent,
z=(k + dk) % z_extent)
# but maybe it isn't in the mask (i.e. air)
if not mask[neighbor.z, neighbor.y, neighbor.x]:
continue
neighbor_index = grid.get_flattened_index(neighbor)
# continuous space displacements
dx = delta_x[k, j, i] * di
dy = delta_y[k, j, i] * dj
dz = delta_z[k, j, i] * dk
inverse_distance2 = 1 / (dx * dx + dy * dy + dz * dz
) # units: 1/(µm^2)
laplacian[voxel_index, voxel_index] -= inverse_distance2
laplacian[voxel_index, neighbor_index] += inverse_distance2
return laplacian.tocsr()
def test_move_1(populated_macrophage: MacrophageCellList,
grid: RectangularGrid, cyto, tissue, fungus_list):
rec_r = 10
cell = populated_macrophage[0]
vox = grid.get_voxel(cell['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
assert cyto.all() == 0
cyto[4, 3, 3] = 10
populated_macrophage.move(rec_r, grid, cyto, tissue, fungus_list)
vox = grid.get_voxel(cell['point'])
assert vox.z == 4 and vox.y == 3 and vox.x == 3
def test_move_1(populated_neutrophil: NeutrophilCellList, grid: RectangularGrid, cyto, tissue):
rec_r = 10
cell = populated_neutrophil[0]
vox = grid.get_voxel(cell['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
assert cyto.all() == 0
cyto[4, 3, 3] = 10
populated_neutrophil.move(rec_r, grid, cyto, tissue)
cell = populated_neutrophil[0]
vox = grid.get_voxel(cell['point'])
assert vox.z == 4 and vox.y == 3 and vox.x == 3
def load(cls, arg: Union[str, bytes, PurePath, IO[bytes]]) -> 'State':
"""Load a pickled state from either a path, a file, or blob of bytes."""
from nlisim.config import SimulationConfig # prevent circular imports
if isinstance(arg, bytes):
arg = BytesIO(arg)
with H5File(arg, 'r') as hf:
time = hf.attrs['time']
grid = RectangularGrid.load(hf)
with StringIO(hf.attrs['config']) as cf:
config = SimulationConfig(cf)
state = cls(time=time, grid=grid, config=config)
for module in config.modules:
group = hf.get(module.name)
if group is None:
raise ValueError(
f'File contains no group for {module.name}')
try:
module_state = module.StateClass.load_state(state, group)
except Exception:
print(f'Error loading state for {module.name}')
raise
state._extra[module.name] = module_state
return state
def test_recruit_new_neutopenic_day_3(neutrophil_list, tissue, grid: RectangularGrid, cyto):
rec_r = 2
rec_rate_ph = 6
granule_count = 5
neutropenic = True
previous_time = 64 # between days 2 -4
# no cytokines
assert cyto[5, 5, 5] == 0
cyto[5, 5, 5] = 2
# test recruit less due to neutropenic
neutrophil_list.recruit_new(
rec_rate_ph, rec_r, granule_count, neutropenic, previous_time, grid, tissue, cyto
)
assert len(neutrophil_list) == 6
# test correct location recruitment
neutropenic = False
neutrophil_list.recruit_new(
rec_rate_ph, rec_r, granule_count, neutropenic, previous_time, grid, tissue, cyto
)
vox = grid.get_voxel(neutrophil_list[-1]['point'])
assert vox.x == 5 and vox.y == 5 and vox.z == 5
assert len(neutrophil_list) == 12
def test_produce_cytokines_0(
neutrophil_list: NeutrophilCellList,
grid: RectangularGrid,
populated_fungus: FungusCellList,
cyto,
):
n_det = 0
n_n = 10
assert cyto[3, 3, 3] == 0
neutrophil_list.append(
NeutrophilCellData.create_cell(
point=Point(x=grid.x[3], y=grid.y[3], z=grid.z[3]),
status=NeutrophilCellData.Status.NONGRANULATING,
granule_count=5,
)
)
vox = grid.get_voxel(neutrophil_list[0]['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
neutrophil_list.produce_cytokines(n_det, n_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 10
def test_damage_hyphae_0(
neutrophil_list: NeutrophilCellList, grid: RectangularGrid, fungus_list: FungusCellList, iron
):
n_det = 0
n_kill = 2
t = 1
health = 100
point = Point(x=35, y=35, z=35)
neutrophil_list.append(
NeutrophilCellData.create_cell(
point=point, status=NeutrophilCellData.Status.NONGRANULATING, granule_count=5
)
)
# hyphae
fungus_list.append(
FungusCellData.create_cell(
point=point, status=FungusCellData.Status.RESTING, form=FungusCellData.Form.HYPHAE
)
)
neutrophil_list.damage_hyphae(n_det, n_kill, t, health, grid, fungus_list, iron)
assert fungus_list[0]['health'] == 50
assert neutrophil_list[0]['granule_count'] == 4
assert neutrophil_list[0]['status'] == NeutrophilCellData.Status.GRANULATING
vox = grid.get_voxel(neutrophil_list[0]['point'])
assert iron[vox.z, vox.y, vox.x] == 0
def test_recruit_new(neutrophil_list, tissue, grid: RectangularGrid, cyto):
rec_r = 2
rec_rate_ph = 2
granule_count = 5
neutropenic = False
previous_time = 1
# no cytokines
assert cyto[5, 5, 5] == 0
cyto[5, 5, 5] = 2
# test correct location recruitment
neutrophil_list.recruit_new(
rec_rate_ph, rec_r, granule_count, neutropenic, previous_time, grid, tissue, cyto
)
vox = grid.get_voxel(neutrophil_list[-1]['point'])
assert len(neutrophil_list) == 2
# TODO: why are x=y=z? what is the point of this?
assert vox.x == 5 and vox.y == 5 and vox.z == 5
# test recruit none due to below threshold
rec_r = 20
rec_rate_ph = 2
neutrophil_list.recruit_new(
rec_rate_ph, rec_r, granule_count, neutropenic, previous_time, grid, tissue, cyto
)
assert len(neutrophil_list) == 2
def test_internalize_conidia_1(epithelium_list: EpitheliumCellList,
grid: RectangularGrid,
fungus_list: FungusCellList):
point = Point(x=35, y=35, z=35)
epithelium_list.append(EpitheliumCellData.create_cell(point=point))
fungus_list.append(
FungusCellData.create_cell(point=point,
status=FungusCellData.Status.RESTING))
vox = grid.get_voxel(epithelium_list[0]['point'])
epithelium_list.internalize_conidia(0, 10, 1, grid, fungus_list)
assert grid.get_voxel(fungus_list[0]['point']) == vox
assert epithelium_list.len_phagosome(0) == 1
assert 0 in epithelium_list[0]['phagosome']
def create(cls, config: 'SimulationConfig'):
"""Generate a new state object from a config."""
shape = (
config.getint('simulation', 'nz'),
config.getint('simulation', 'ny'),
config.getint('simulation', 'nx'),
)
spacing = (
config.getfloat('simulation', 'dz'),
config.getfloat('simulation', 'dy'),
config.getfloat('simulation', 'dx'),
)
grid = RectangularGrid.construct_uniform(shape, spacing)
state = State(time=0.0, grid=grid, config=config)
for module in state.config.modules:
if hasattr(state, module.name):
# prevent modules from overriding existing class attributes
raise ValueError(
f'The name "{module.name}" is a reserved token.')
with validation_context(f'{module.name} (construction)'):
state._extra[module.name] = module.StateClass(
global_state=state)
module.construct(state)
return state
def test_recruit_new(macrophage_list, tissue, grid: RectangularGrid, cyto):
rec_r = 2
p_rec_r = 1.0
rec_rate_ph = 2
# no cytokines
assert cyto[1, 2, 3] == 0
cyto[1, 2, 3] = 2
# test correct location recruitment
macrophage_list.recruit_new(rec_rate_ph, rec_r, p_rec_r, tissue, grid,
cyto)
vox = grid.get_voxel(macrophage_list[-1]['point'])
assert len(macrophage_list) == 2
assert vox.x == 3 and vox.y == 2 and vox.z == 1
# test recruit none due to below threshold
rec_r = 20
p_rec_r = 1.0
rec_rate_ph = 2
macrophage_list.recruit_new(rec_rate_ph, rec_r, p_rec_r, tissue, grid,
cyto)
assert len(macrophage_list) == 2
def discrete_laplacian(grid: RectangularGrid,
mask: np.ndarray,
dtype: np.dtype = np.float64) -> csr_matrix:
"""Return a discrete laplacian operator for the given restricted grid.
This computes a standard laplacian operator as a scipy linear operator, except it is
restricted to a grid mask. The use case for this is to compute surface diffusion
on a gridded variable. The mask is generated from a category on the lung_tissue
variable.
"""
graph_shape = len(grid), len(grid)
laplacian = dok_matrix(graph_shape)
delta_z = grid.delta(0)
delta_y = grid.delta(1)
delta_x = grid.delta(2)
for k, j, i in zip(*(mask).nonzero()):
voxel = Voxel(x=i, y=j, z=k)
voxel_index = grid.get_flattened_index(voxel)
normalization = 0
for neighbor in grid.get_adjecent_voxels(voxel, corners=False):
ni = neighbor.x
nj = neighbor.y
nk = neighbor.z
if not mask[nk, nj, ni]:
continue
neighbor_index = grid.get_flattened_index(neighbor)
dx = delta_x[k, j, i] * (i - ni)
dy = delta_y[k, j, i] * (j - nj)
dz = delta_z[k, j, i] * (k - nk)
distance2 = 1 / (dx * dx + dy * dy + dz * dz)
normalization -= distance2
laplacian[voxel_index, neighbor_index] = distance2
laplacian[voxel_index, voxel_index] = normalization
return laplacian.tocsr()
def test_move_cell(grid: RectangularGrid):
point = Point(x=4.5, y=4.5, z=4.5)
raw_cells = [CellData.create_cell(point=point) for _ in range(5)]
raw_cells[1]['point'] = Point(x=-1, y=4.5, z=4.5)
raw_cells[4]['point'] = Point(x=4.5, y=4.5, z=-1)
cells = CellList(grid=grid)
cells.extend(raw_cells)
cells[0]['point'] = Point(x=50, y=50, z=50)
# updating an incorrect index will not update the cell at index 0
cells.update_voxel_index([1, 3])
assert_array_equal(cells.get_neighboring_cells(cells[2]), [0, 2, 3])
assert cells._reverse_voxel_index[0] == grid.get_voxel(point)
# this should correctly update the voxel index
cells.update_voxel_index([0])
assert_array_equal(cells.get_neighboring_cells(cells[0]), [0])
assert cells._reverse_voxel_index[0] == grid.get_voxel(cells[0]['point'])
def test_internalize_and_move(
macrophage_list: MacrophageCellList,
grid: RectangularGrid,
fungus_list: FungusCellList,
cyto,
tissue,
):
point = Point(x=35, y=35, z=35)
macrophage_list.append(MacrophageCellData.create_cell(point=point))
fungus_list.append(
FungusCellData.create_cell(point=point,
status=FungusCellData.Status.RESTING))
fungus_list.append(
FungusCellData.create_cell(point=point,
status=FungusCellData.Status.RESTING))
macrophage_list.internalize_conidia(1, 50, 1, grid, fungus_list)
assert fungus_list.cell_data['internalized'][0]
assert fungus_list.cell_data['internalized'][1]
assert macrophage_list.len_phagosome(0) == 2
rec_r = 10
cell = macrophage_list[0]
vox = grid.get_voxel(cell['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
assert cyto.all() == 0
cyto[4, 3, 3] = 10
macrophage_list.move(rec_r, grid, cyto, tissue, fungus_list)
vox = grid.get_voxel(cell['point'])
assert vox.z == 4 and vox.y == 3 and vox.x == 3
for f in fungus_list:
vox = grid.get_voxel(f['point'])
assert vox.z == 4 and vox.y == 3 and vox.x == 3
def test_internalize_conidia_none(
populated_epithelium: EpitheliumCellList,
grid: RectangularGrid,
fungus_list: FungusCellList,
):
cell = populated_epithelium[0]
vox = grid.get_voxel(cell['point'])
assert len(fungus_list.get_cells_in_voxel(vox)) == 0
populated_epithelium.internalize_conidia(0, 10, 1, grid, fungus_list)
assert populated_epithelium.len_phagosome(0) == 0
for v in cell['phagosome']:
assert v == -1
def __init__(self, shape: ShapeType, space: SpacingType, scale: int,
randomness: int):
self.scale = scale
self.randomness = randomness
self.shape = (shape[0] * scale, shape[1] * scale, shape[2] * scale)
self.space = space
self.grid = RectangularGrid.construct_uniform(self.shape, self.space)
self.geo = self.grid.allocate_variable(dtype=np.dtype(np.int8))
self.geo.fill(2)
self.fixed = np.zeros(self.shape)
self.duct_f: List[Union[Sphere, Cylinder]] = []
self.sac_f: List[Union[Sphere, Cylinder]] = []
def test_internalize_conidia_none(
populated_macrophage: MacrophageCellList,
grid: RectangularGrid,
populated_fungus: FungusCellList,
):
m_det = 0
cell = populated_macrophage[0]
vox = grid.get_voxel(cell['point'])
assert len(populated_fungus.get_cells_in_voxel(vox)) == 1
populated_macrophage.internalize_conidia(m_det, 50, 1, grid,
populated_fungus)
assert populated_macrophage.len_phagosome(0) == 0
for v in cell['phagosome']:
assert v == -1
def test_recruit_new_multiple_locations(macrophage_list: MacrophageCellList,
tissue, grid: RectangularGrid, cyto):
rec_r = 2
p_rec_r = 1.0
rec_rate_ph = 50
cyto[1, 2, 3] = 2
cyto[4, 5, 6] = 2
macrophage_list.recruit_new(rec_rate_ph, rec_r, p_rec_r, tissue, grid,
cyto)
assert len(macrophage_list) == 50
for cell in macrophage_list.cell_data:
vox = grid.get_voxel(cell['point'])
assert vox.x in [3, 6] and vox.y in [2, 5] and vox.z in [1, 4]
def kill_fungal_cell(
afumigatus: AfumigatusState,
afumigatus_cell: AfumigatusCellData,
afumigatus_cell_index: int,
iron: IronState,
grid: RectangularGrid,
):
"""Kill a fungal cell.
Unlinks the cell from its fungal tree and releases its iron.
"""
# unlink from any children
if afumigatus_cell['next_septa'] != -1:
next_septa = afumigatus_cell['next_septa']
afumigatus_cell['next_septa'] = -1
afumigatus.cells[next_septa]['is_root'] = True
afumigatus.cells[next_septa]['previous_septa'] = -1
if afumigatus_cell['next_branch'] != -1:
next_branch = afumigatus_cell['next_branch']
afumigatus_cell['next_branch'] = -1
afumigatus.cells[next_branch]['is_root'] = True
afumigatus.cells[next_branch]['previous_septa'] = -1
# unlink from parent, if exists
parent_id = afumigatus_cell['previous_septa']
if parent_id != -1:
afumigatus_cell['previous_septa'] = -1
parent_cell: AfumigatusCellData = afumigatus.cells[parent_id]
if parent_cell['next_septa'] == afumigatus_cell_index:
parent_cell['next_septa'] = -1
elif parent_cell['next_branch'] == afumigatus_cell_index:
parent_cell['next_branch'] = -1
else:
raise AssertionError("The fungal tree structure is malformed.")
# kill the cell off and release its iron
voxel: Voxel = grid.get_voxel(afumigatus_cell['point'])
iron.grid[voxel.z, voxel.y, voxel.x] += afumigatus_cell['iron_pool']
afumigatus_cell['iron_pool'] = 0.0
afumigatus_cell['dead'] = True
afumigatus_cell['status'] = AfumigatusCellStatus.DEAD
def test_recruit_new_multiple_locations(
neutrophil_list: NeutrophilCellList, tissue, grid: RectangularGrid, cyto
):
rec_r = 2
rec_rate_ph = 50
granule_count = 5
neutropenic = False
previous_time = 1
cyto[5, 5, 5] = 2
cyto[4, 5, 5] = 2
neutrophil_list.recruit_new(
rec_rate_ph, rec_r, granule_count, neutropenic, previous_time, grid, tissue, cyto
)
assert len(neutrophil_list) == 50
for cell in neutrophil_list.cell_data:
vox = grid.get_voxel(cell['point'])
assert vox.x == 5 and vox.y == 5 and vox.z in [4, 5]
def create(cls, config: 'SimulationConfig'):
"""Generate a new state object from a config."""
voxel_volume = config.getfloat('simulation', 'voxel_volume')
lung_tissue = get_geometry_file(
config.get('simulation', 'geometry_path'))
# python type checker isn't enough to understand this
assert len(lung_tissue.shape) == 3
# noinspection PyTypeChecker
shape: Tuple[int, int, int] = lung_tissue.shape
space_volume = voxel_volume * np.product(shape)
spacing = (
config.getfloat('simulation', 'dz'),
config.getfloat('simulation', 'dy'),
config.getfloat('simulation', 'dx'),
)
grid = RectangularGrid.construct_uniform(shape, spacing)
state = State(
time=0.0,
grid=grid,
config=config,
lung_tissue=lung_tissue,
voxel_volume=voxel_volume,
space_volume=space_volume,
)
for module in state.config.modules:
if hasattr(state, module.name):
# prevent modules from overriding existing class attributes
raise ValueError(
f'The name "{module.name}" is a reserved token.')
with validation_context(f'{module.name} (construction)'):
state._extra[module.name] = module.StateClass(
global_state=state)
module.construct(state)
return state
def test_produce_cytokines_0(
macrophage_list: MacrophageCellList,
grid: RectangularGrid,
populated_fungus: FungusCellList,
cyto,
):
m_det = 0
m_n = 10
assert cyto[3, 3, 3] == 0
macrophage_list.append(
MacrophageCellData.create_cell(point=Point(x=grid.x[3],
y=grid.y[3],
z=grid.z[3]), ))
vox = grid.get_voxel(macrophage_list[0]['point'])
assert vox.z == 3 and vox.y == 3 and vox.x == 3
macrophage_list.produce_cytokines(m_det, m_n, grid, populated_fungus, cyto)
assert cyto[3, 3, 3] == 10
def grid():
# a 100 x 100 x 100 unit grid
yield RectangularGrid.construct_uniform((10, 10, 10), (10, 10, 10))
def test_get_flattened_index(voxel, index, grid: RectangularGrid):
assert grid.get_flattened_index(voxel) == index
assert grid.voxel_from_flattened_index(index) == voxel
def test_get_voxel(grid: RectangularGrid, point, voxel):
assert grid.get_voxel(point) == voxel
def test_valid_voxel(grid: RectangularGrid, voxel, valid):
assert grid.is_valid_voxel(voxel) == valid
def test_get_adjacent_voxels(grid: RectangularGrid, voxel, neighbors):
assert set(grid.get_adjacent_voxels(voxel)) == neighbors
