Module nlisim.oldmodules.fungus
Expand source code
from enum import IntEnum
from typing import Any, Dict, Tuple
import attr
import numpy as np
from nlisim.cell import CellData, CellList
from nlisim.coordinates import Point, Voxel
from nlisim.module import ModuleModel, ModuleState
from nlisim.random import rg
from nlisim.state import State
from nlisim.util import TissueType
class FungusCellData(CellData):
class Status(IntEnum):
DRIFTING = 99
RESTING = 0 # CONIDIA relevant
SWOLLEN = 1 # CONIDIA relevant
GERMINATED = 2 # CONIDIA relevant
GROWABLE = 3 # HYPHAE relevant
GROWN = 4 # HYPHAE relevant
DEAD = 5
class Form(IntEnum):
CONIDIA = 0
HYPHAE = 1
FUNGUS_FIELDS = [
('form', 'u1'),
('status', 'u1'),
('iteration', 'i4'),
('mobile', 'b1'),
('internalized', 'b1'),
('iron', 'f8'),
('health', 'f8'),
]
dtype = np.dtype(CellData.FIELDS + FUNGUS_FIELDS, align=True) # type: ignore
@classmethod
def create_cell_tuple(
cls,
*,
iron: float = 0,
status: Status = Status.RESTING,
form: Form = Form.CONIDIA,
iteration=0,
mobile=False,
internalized=False,
health=100,
**kwargs,
) -> Tuple:
return CellData.create_cell_tuple(**kwargs) + (
form,
status,
iteration,
mobile,
internalized,
iron,
health,
)
@attr.s(kw_only=True, frozen=True, repr=False)
class FungusCellList(CellList):
CellDataClass = FungusCellData
def iron_uptake(self, iron: np.ndarray, iron_max: float, iron_min: float, iron_absorb: float):
"""Absorb iron from external environment."""
cells = self.cell_data
for vox_index in np.argwhere(iron > iron_min):
vox = Voxel(x=vox_index[2], y=vox_index[1], z=vox_index[0])
cells_here = self.get_cells_in_voxel(vox)
indices = []
for index in cells_here:
if (
cells[index]['form'] == FungusCellData.Form.HYPHAE.value
and np.invert(cells[index]['internalized'])
and cells[index]['iron'] < iron_max
):
indices.append(index)
if len(indices) > 0:
iron_split = iron_absorb * (iron[vox.z, vox.y, vox.x] / len(indices))
for cell_index in indices:
cells[cell_index]['iron'] += iron_split
if cells[cell_index]['iron'] > iron_max:
cells[cell_index]['iron'] = iron_max
iron[vox.z, vox.y, vox.x] = (1 - iron_absorb) * iron[vox.z, vox.y, vox.x]
def spawn_hypahael_cell(self, children):
children['status'] = FungusCellData.Status.GROWABLE
children['form'] = FungusCellData.Form.HYPHAE
children['mobile'] = False
self.extend(children)
def spawn_spores(self, points):
n, m = points.shape
if m != 3:
raise ValueError('Invalid shape for a point object')
spores = FungusCellData(n, initialize=True)
spores['point'] = points
spores['status'] = FungusCellData.Status.RESTING
self.extend(spores)
def initialize_spores(self, tissue: np.ndarray, init_num: int):
"""Initialize spores on epithelium cells."""
grid = self.grid
if init_num > 0:
points = np.zeros((init_num, 3))
indices = np.argwhere(tissue == TissueType.EPITHELIUM.value)
if len(indices) > 0:
rg.shuffle(indices)
for i in range(init_num):
# putting in some protection for the occasional time that we place the cell on
# the boundary of the voxel-space
if indices[i][2] == grid.xv.shape[0] - 1:
x = grid.xv[indices[i][2]]
else:
x = rg.uniform(grid.xv[indices[i][2]], grid.xv[indices[i][2] + 1])
if indices[i][1] == grid.yv.shape[0] - 1:
y = grid.yv[indices[i][1]]
else:
y = rg.uniform(grid.yv[indices[i][1]], grid.yv[indices[i][1] + 1])
if indices[i][0] == grid.zv.shape[0] - 1:
z = grid.zv[indices[i][0]]
else:
z = rg.uniform(grid.zv[indices[i][0]], grid.zv[indices[i][0] + 1])
point = Point(x=x, y=y, z=z)
points[i] = point
self.spawn_spores(points)
def grow_hyphae(self, iron_min_grow, grow_time, p_branch, spacing):
"""Grow fungal hyphae."""
cells = self.cell_data
conidia_indices = self.alive(
(cells['form'] == FungusCellData.Form.CONIDIA)
& (cells['status'] == FungusCellData.Status.GERMINATED)
& (np.invert(cells['internalized']))
)
hyphae_indices = self.alive(
(cells['form'] == FungusCellData.Form.HYPHAE)
& (cells['status'] == FungusCellData.Status.GROWABLE)
& (np.invert(cells['internalized']))
& (cells['iron'] > iron_min_grow)
& (cells['iteration'] > grow_time)
)
# grow conidia
if len(conidia_indices) != 0:
cells['status'][conidia_indices] = FungusCellData.Status.GROWN
cells['form'][conidia_indices] = FungusCellData.Form.HYPHAE
children = FungusCellData(len(conidia_indices), initialize=True)
children['iron'] = cells['iron'][conidia_indices]
growth = spacing * (rg.random((len(conidia_indices), 3)) * 2 - 1)
children['point'] = cells['point'][conidia_indices] + growth
self.spawn_hypahael_cell(children)
# grow hyphae
if len(hyphae_indices) != 0:
cells['status'][hyphae_indices] = FungusCellData.Status.GROWN
branch_mask = rg.random(len(hyphae_indices)) < p_branch
not_branch_indices = (np.invert(branch_mask)).nonzero()[0]
branch_indices = branch_mask.nonzero()[0]
elongate_children = FungusCellData(len(hyphae_indices), initialize=True)
branch_children = FungusCellData(len(branch_indices), initialize=True)
elongate_children['iron'] = cells['iron'][hyphae_indices] / 2
growth = spacing * (rg.random((len(hyphae_indices), 3)) * 2 - 1)
elongate_children['point'] = cells['point'][hyphae_indices] + growth
if len(branch_indices) != 0:
elongate_children['iron'][branch_indices] = (
cells['iron'][hyphae_indices[branch_indices]] / 3
)
branch_children['iron'] = cells['iron'][hyphae_indices[branch_indices]] / 3
growth = spacing * (rg.random((len(hyphae_indices[branch_indices]), 3)) * 2 - 1)
branch_children['point'] = cells['point'][hyphae_indices[branch_indices]] + growth
# update iron in orignal cells
cells['iron'][hyphae_indices[not_branch_indices]] /= 2
cells['iron'][hyphae_indices[branch_indices]] /= 3
self.spawn_hypahael_cell(elongate_children)
self.spawn_hypahael_cell(branch_children)
def age(self):
"""Add one iteration to all alive cells."""
np.add.at(self.cell_data['iteration'], self.alive(), 1)
def kill(self):
"""If a cell have 0 health point or out of range, kill the cell."""
cells = self.cell_data
mask = cells.point_mask(cells['point'], self.grid)
indices = self.alive(np.logical_or(cells['health'] <= 0, np.invert(mask)))
cells['status'][indices] = FungusCellData.Status.DEAD
cells['dead'][indices] = True
def change_status(self, p_internal_swell: float, rest_time: int, swell_time: int):
cells = self.cell_data
indices = self.alive(
cells['form'] != FungusCellData.Form.HYPHAE,
)
internalized_indices = (cells['internalized'][indices]).nonzero()[0]
not_internalized_indices = (np.invert(cells['internalized'][indices])).nonzero()[0]
internalized_rest_indices = np.logical_and(
cells['status'][internalized_indices] == FungusCellData.Status.RESTING,
cells['iteration'][internalized_indices] >= rest_time,
).nonzero()[0]
internalized_swollen_indices = np.logical_and(
cells['status'][internalized_indices] == FungusCellData.Status.SWOLLEN,
cells['iteration'][internalized_indices] >= swell_time,
).nonzero()[0]
# internal fungus with REST status
swall_mask = rg.random(len(internalized_rest_indices)) < p_internal_swell
internalized_rest_indices = swall_mask.nonzero()[0]
cells['status'][internalized_rest_indices] = FungusCellData.Status.SWOLLEN
cells['iteration'][internalized_rest_indices] = 0
# internal fungus with SWOLLEN status
cells['status'][internalized_swollen_indices] = FungusCellData.Status.GERMINATED
cells['iteration'][internalized_swollen_indices] = 0
rest_indices = np.logical_and(
cells['status'][not_internalized_indices] == FungusCellData.Status.RESTING,
cells['iteration'][not_internalized_indices] >= rest_time,
).nonzero()[0]
swollen_indices = np.logical_and(
cells['status'][not_internalized_indices] == FungusCellData.Status.SWOLLEN,
cells['iteration'][not_internalized_indices] >= swell_time,
).nonzero()[0]
# free fungus with REST status
cells['status'][rest_indices] = FungusCellData.Status.SWOLLEN
cells['iteration'][rest_indices] = 0
# free fungus with SWOLLEN status
cells['status'][swollen_indices] = FungusCellData.Status.GERMINATED
cells['iteration'][swollen_indices] = 0
def cell_list_factory(self: 'FungusState'):
return FungusCellList(grid=self.global_state.grid)
@attr.s(kw_only=True)
class FungusState(ModuleState):
cells: FungusCellList = attr.ib(default=attr.Factory(cell_list_factory, takes_self=True))
# init_num: int = 0
# p_lodge: float = 0
# p_internal_swell: float = 0.05
# iron_min: int = 0
# iron_max: float = 0.0
# iron_absorb: float = 0.0
# spacing: float = 0.0
# iron_min_grow: float = 0.0
# grow_time: float = 0.0
# p_branch: float = 0.0
# p_internalize: float = 0.0
health: float = 100.0
class Fungus(ModuleModel):
name = 'fungus'
StateClass = FungusState
def initialize(self, state: State):
fungus: FungusState = state.fungus
# grid: RectangularGrid = state.grid
tissue = state.geometry.lung_tissue
self.init_num = self.config.getint('init_num')
self.p_lodge = self.config.getfloat('p_lodge')
self.p_internal_swell = self.config.getfloat('p_internal_swell')
self.iron_min = self.config.getint('iron_min')
self.iron_max = self.config.getfloat('iron_max')
self.iron_absorb = self.config.getfloat('iron_absorb')
self.spacing = self.config.getfloat('spacing')
self.iron_min_grow = self.config.getfloat('iron_min_grow')
self.p_branch = self.config.getfloat('p_branch')
self.p_internalize = self.config.getfloat('p_internalize')
self.rest_time = self.config.getint('rest_time')
self.swell_time = self.config.getint('swell_time')
self.grow_time = self.config.getint('grow_time')
fungus.health = self.config.getfloat('init_health')
cells = fungus.cells
cells.initialize_spores(tissue, self.init_num)
return state
def advance(self, state: State, previous_time: float):
cells = state.fungus.cells
cells.kill() # clear dead cell
cells.age()
cells.change_status(self.p_internal_swell, self.rest_time, self.swell_time)
if hasattr(state, 'molecules'):
iron = state.molecules.grid['iron']
cells.iron_uptake(iron, self.iron_max, self.iron_min, self.iron_absorb)
cells.grow_hyphae(self.iron_min_grow, self.grow_time, self.p_branch, self.spacing)
return state
def summary_stats(self, state: State) -> Dict[str, Any]:
fungus: FungusState = state.fungus
num_conidia: int = 0
num_hyphae: int = 0
total_iron: float = 0.0
for cell_index in fungus.cells.alive():
cell: FungusCellData = fungus.cells[cell_index]
if cell['form'] == FungusCellData.Form.HYPHAE:
num_hyphae += 1
elif cell['form'] == FungusCellData.Form.CONIDIA:
num_conidia += 1
total_iron += cell['iron']
return {
'count': len(fungus.cells.alive()),
'conidia': int(num_conidia),
'hyphae': int(num_hyphae),
'total_iron': float(total_iron),
}
def visualization_data(self, state: State) -> Tuple[str, Any]:
return 'cells', state.fungus.cellsFunctions
def cell_list_factory(self: FungusState)-
Expand source code
def cell_list_factory(self: 'FungusState'): return FungusCellList(grid=self.global_state.grid)
Classes
class Fungus (config: SimulationConfig)-
Expand source code
class Fungus(ModuleModel): name = 'fungus' StateClass = FungusState def initialize(self, state: State): fungus: FungusState = state.fungus # grid: RectangularGrid = state.grid tissue = state.geometry.lung_tissue self.init_num = self.config.getint('init_num') self.p_lodge = self.config.getfloat('p_lodge') self.p_internal_swell = self.config.getfloat('p_internal_swell') self.iron_min = self.config.getint('iron_min') self.iron_max = self.config.getfloat('iron_max') self.iron_absorb = self.config.getfloat('iron_absorb') self.spacing = self.config.getfloat('spacing') self.iron_min_grow = self.config.getfloat('iron_min_grow') self.p_branch = self.config.getfloat('p_branch') self.p_internalize = self.config.getfloat('p_internalize') self.rest_time = self.config.getint('rest_time') self.swell_time = self.config.getint('swell_time') self.grow_time = self.config.getint('grow_time') fungus.health = self.config.getfloat('init_health') cells = fungus.cells cells.initialize_spores(tissue, self.init_num) return state def advance(self, state: State, previous_time: float): cells = state.fungus.cells cells.kill() # clear dead cell cells.age() cells.change_status(self.p_internal_swell, self.rest_time, self.swell_time) if hasattr(state, 'molecules'): iron = state.molecules.grid['iron'] cells.iron_uptake(iron, self.iron_max, self.iron_min, self.iron_absorb) cells.grow_hyphae(self.iron_min_grow, self.grow_time, self.p_branch, self.spacing) return state def summary_stats(self, state: State) -> Dict[str, Any]: fungus: FungusState = state.fungus num_conidia: int = 0 num_hyphae: int = 0 total_iron: float = 0.0 for cell_index in fungus.cells.alive(): cell: FungusCellData = fungus.cells[cell_index] if cell['form'] == FungusCellData.Form.HYPHAE: num_hyphae += 1 elif cell['form'] == FungusCellData.Form.CONIDIA: num_conidia += 1 total_iron += cell['iron'] return { 'count': len(fungus.cells.alive()), 'conidia': int(num_conidia), 'hyphae': int(num_hyphae), 'total_iron': float(total_iron), } def visualization_data(self, state: State) -> Tuple[str, Any]: return 'cells', state.fungus.cellsAncestors
Inherited members
class FungusCellData (arg: Union[int, Iterable[ForwardRef('CellData')]], initialize: bool = False, **kwargs)-
A low-level data contain for an array cells.
This class is a subtype of numpy.recarray containing the lowest level representation of a list of "cells" in a simulation. The underlying data format of this type are identical to a simple array of C structures with the fields given in the static "dtype" variable.
The base class contains only a single coordinate representing the location of the center of the cell. Most implementations will want to override this class to append more fields. Subclasses must also override the base implementation of
create_cellto construct a single record containing the additional fields.For example, the following derived class adds an addition floating point value associated with each cell.
class DerivedCell(CellData): FIELDS = CellData.FIELDS + [ ('iron_content', 'f8') ] dtype = np.dtype(CellData.FIELDS, align=True) @classmethod def create_cell_tuple(cls, iron_content=0, **kwargs) -> Tuple: return CellData.create_cell_tuple(**kwargs) + (iron_content,)Expand source code
class FungusCellData(CellData): class Status(IntEnum): DRIFTING = 99 RESTING = 0 # CONIDIA relevant SWOLLEN = 1 # CONIDIA relevant GERMINATED = 2 # CONIDIA relevant GROWABLE = 3 # HYPHAE relevant GROWN = 4 # HYPHAE relevant DEAD = 5 class Form(IntEnum): CONIDIA = 0 HYPHAE = 1 FUNGUS_FIELDS = [ ('form', 'u1'), ('status', 'u1'), ('iteration', 'i4'), ('mobile', 'b1'), ('internalized', 'b1'), ('iron', 'f8'), ('health', 'f8'), ] dtype = np.dtype(CellData.FIELDS + FUNGUS_FIELDS, align=True) # type: ignore @classmethod def create_cell_tuple( cls, *, iron: float = 0, status: Status = Status.RESTING, form: Form = Form.CONIDIA, iteration=0, mobile=False, internalized=False, health=100, **kwargs, ) -> Tuple: return CellData.create_cell_tuple(**kwargs) + ( form, status, iteration, mobile, internalized, iron, health, )Ancestors
- CellData
- numpy.ndarray
Class variables
var FUNGUS_FIELDSvar Form-
An enumeration.
var Status-
An enumeration.
Inherited members
class FungusCellList (*, grid: RectangularGrid, max_cells: int = 1000000, cell_data: CellData = NOTHING)-
A python view on top of a CellData array.
This class represents a pythonic interface to the data contained in a CellData array. Because the CellData class is a low-level object, it does not allow dynamically appending new elements. Objects of this class get around this limitation by pre-allocating a large block of memory that is transparently available. User-facing properties are sliced to make it appear as if the extra data is not there.
Subclassed types are expected to set the
CellDataClassattribute to a subclass ofCellData. This provides information about the underlying low-level array.Parameters
grid:simulation.grid.RectangularGridmax_cells:int, optionalcells:simulation.cell.CellData, optional
Method generated by attrs for class FungusCellList.
Expand source code
class FungusCellList(CellList): CellDataClass = FungusCellData def iron_uptake(self, iron: np.ndarray, iron_max: float, iron_min: float, iron_absorb: float): """Absorb iron from external environment.""" cells = self.cell_data for vox_index in np.argwhere(iron > iron_min): vox = Voxel(x=vox_index[2], y=vox_index[1], z=vox_index[0]) cells_here = self.get_cells_in_voxel(vox) indices = [] for index in cells_here: if ( cells[index]['form'] == FungusCellData.Form.HYPHAE.value and np.invert(cells[index]['internalized']) and cells[index]['iron'] < iron_max ): indices.append(index) if len(indices) > 0: iron_split = iron_absorb * (iron[vox.z, vox.y, vox.x] / len(indices)) for cell_index in indices: cells[cell_index]['iron'] += iron_split if cells[cell_index]['iron'] > iron_max: cells[cell_index]['iron'] = iron_max iron[vox.z, vox.y, vox.x] = (1 - iron_absorb) * iron[vox.z, vox.y, vox.x] def spawn_hypahael_cell(self, children): children['status'] = FungusCellData.Status.GROWABLE children['form'] = FungusCellData.Form.HYPHAE children['mobile'] = False self.extend(children) def spawn_spores(self, points): n, m = points.shape if m != 3: raise ValueError('Invalid shape for a point object') spores = FungusCellData(n, initialize=True) spores['point'] = points spores['status'] = FungusCellData.Status.RESTING self.extend(spores) def initialize_spores(self, tissue: np.ndarray, init_num: int): """Initialize spores on epithelium cells.""" grid = self.grid if init_num > 0: points = np.zeros((init_num, 3)) indices = np.argwhere(tissue == TissueType.EPITHELIUM.value) if len(indices) > 0: rg.shuffle(indices) for i in range(init_num): # putting in some protection for the occasional time that we place the cell on # the boundary of the voxel-space if indices[i][2] == grid.xv.shape[0] - 1: x = grid.xv[indices[i][2]] else: x = rg.uniform(grid.xv[indices[i][2]], grid.xv[indices[i][2] + 1]) if indices[i][1] == grid.yv.shape[0] - 1: y = grid.yv[indices[i][1]] else: y = rg.uniform(grid.yv[indices[i][1]], grid.yv[indices[i][1] + 1]) if indices[i][0] == grid.zv.shape[0] - 1: z = grid.zv[indices[i][0]] else: z = rg.uniform(grid.zv[indices[i][0]], grid.zv[indices[i][0] + 1]) point = Point(x=x, y=y, z=z) points[i] = point self.spawn_spores(points) def grow_hyphae(self, iron_min_grow, grow_time, p_branch, spacing): """Grow fungal hyphae.""" cells = self.cell_data conidia_indices = self.alive( (cells['form'] == FungusCellData.Form.CONIDIA) & (cells['status'] == FungusCellData.Status.GERMINATED) & (np.invert(cells['internalized'])) ) hyphae_indices = self.alive( (cells['form'] == FungusCellData.Form.HYPHAE) & (cells['status'] == FungusCellData.Status.GROWABLE) & (np.invert(cells['internalized'])) & (cells['iron'] > iron_min_grow) & (cells['iteration'] > grow_time) ) # grow conidia if len(conidia_indices) != 0: cells['status'][conidia_indices] = FungusCellData.Status.GROWN cells['form'][conidia_indices] = FungusCellData.Form.HYPHAE children = FungusCellData(len(conidia_indices), initialize=True) children['iron'] = cells['iron'][conidia_indices] growth = spacing * (rg.random((len(conidia_indices), 3)) * 2 - 1) children['point'] = cells['point'][conidia_indices] + growth self.spawn_hypahael_cell(children) # grow hyphae if len(hyphae_indices) != 0: cells['status'][hyphae_indices] = FungusCellData.Status.GROWN branch_mask = rg.random(len(hyphae_indices)) < p_branch not_branch_indices = (np.invert(branch_mask)).nonzero()[0] branch_indices = branch_mask.nonzero()[0] elongate_children = FungusCellData(len(hyphae_indices), initialize=True) branch_children = FungusCellData(len(branch_indices), initialize=True) elongate_children['iron'] = cells['iron'][hyphae_indices] / 2 growth = spacing * (rg.random((len(hyphae_indices), 3)) * 2 - 1) elongate_children['point'] = cells['point'][hyphae_indices] + growth if len(branch_indices) != 0: elongate_children['iron'][branch_indices] = ( cells['iron'][hyphae_indices[branch_indices]] / 3 ) branch_children['iron'] = cells['iron'][hyphae_indices[branch_indices]] / 3 growth = spacing * (rg.random((len(hyphae_indices[branch_indices]), 3)) * 2 - 1) branch_children['point'] = cells['point'][hyphae_indices[branch_indices]] + growth # update iron in orignal cells cells['iron'][hyphae_indices[not_branch_indices]] /= 2 cells['iron'][hyphae_indices[branch_indices]] /= 3 self.spawn_hypahael_cell(elongate_children) self.spawn_hypahael_cell(branch_children) def age(self): """Add one iteration to all alive cells.""" np.add.at(self.cell_data['iteration'], self.alive(), 1) def kill(self): """If a cell have 0 health point or out of range, kill the cell.""" cells = self.cell_data mask = cells.point_mask(cells['point'], self.grid) indices = self.alive(np.logical_or(cells['health'] <= 0, np.invert(mask))) cells['status'][indices] = FungusCellData.Status.DEAD cells['dead'][indices] = True def change_status(self, p_internal_swell: float, rest_time: int, swell_time: int): cells = self.cell_data indices = self.alive( cells['form'] != FungusCellData.Form.HYPHAE, ) internalized_indices = (cells['internalized'][indices]).nonzero()[0] not_internalized_indices = (np.invert(cells['internalized'][indices])).nonzero()[0] internalized_rest_indices = np.logical_and( cells['status'][internalized_indices] == FungusCellData.Status.RESTING, cells['iteration'][internalized_indices] >= rest_time, ).nonzero()[0] internalized_swollen_indices = np.logical_and( cells['status'][internalized_indices] == FungusCellData.Status.SWOLLEN, cells['iteration'][internalized_indices] >= swell_time, ).nonzero()[0] # internal fungus with REST status swall_mask = rg.random(len(internalized_rest_indices)) < p_internal_swell internalized_rest_indices = swall_mask.nonzero()[0] cells['status'][internalized_rest_indices] = FungusCellData.Status.SWOLLEN cells['iteration'][internalized_rest_indices] = 0 # internal fungus with SWOLLEN status cells['status'][internalized_swollen_indices] = FungusCellData.Status.GERMINATED cells['iteration'][internalized_swollen_indices] = 0 rest_indices = np.logical_and( cells['status'][not_internalized_indices] == FungusCellData.Status.RESTING, cells['iteration'][not_internalized_indices] >= rest_time, ).nonzero()[0] swollen_indices = np.logical_and( cells['status'][not_internalized_indices] == FungusCellData.Status.SWOLLEN, cells['iteration'][not_internalized_indices] >= swell_time, ).nonzero()[0] # free fungus with REST status cells['status'][rest_indices] = FungusCellData.Status.SWOLLEN cells['iteration'][rest_indices] = 0 # free fungus with SWOLLEN status cells['status'][swollen_indices] = FungusCellData.Status.GERMINATED cells['iteration'][swollen_indices] = 0Ancestors
Class variables
var grid : RectangularGridvar max_cells : int
Methods
def age(self)-
Add one iteration to all alive cells.
Expand source code
def age(self): """Add one iteration to all alive cells.""" np.add.at(self.cell_data['iteration'], self.alive(), 1) def change_status(self, p_internal_swell: float, rest_time: int, swell_time: int)-
Expand source code
def change_status(self, p_internal_swell: float, rest_time: int, swell_time: int): cells = self.cell_data indices = self.alive( cells['form'] != FungusCellData.Form.HYPHAE, ) internalized_indices = (cells['internalized'][indices]).nonzero()[0] not_internalized_indices = (np.invert(cells['internalized'][indices])).nonzero()[0] internalized_rest_indices = np.logical_and( cells['status'][internalized_indices] == FungusCellData.Status.RESTING, cells['iteration'][internalized_indices] >= rest_time, ).nonzero()[0] internalized_swollen_indices = np.logical_and( cells['status'][internalized_indices] == FungusCellData.Status.SWOLLEN, cells['iteration'][internalized_indices] >= swell_time, ).nonzero()[0] # internal fungus with REST status swall_mask = rg.random(len(internalized_rest_indices)) < p_internal_swell internalized_rest_indices = swall_mask.nonzero()[0] cells['status'][internalized_rest_indices] = FungusCellData.Status.SWOLLEN cells['iteration'][internalized_rest_indices] = 0 # internal fungus with SWOLLEN status cells['status'][internalized_swollen_indices] = FungusCellData.Status.GERMINATED cells['iteration'][internalized_swollen_indices] = 0 rest_indices = np.logical_and( cells['status'][not_internalized_indices] == FungusCellData.Status.RESTING, cells['iteration'][not_internalized_indices] >= rest_time, ).nonzero()[0] swollen_indices = np.logical_and( cells['status'][not_internalized_indices] == FungusCellData.Status.SWOLLEN, cells['iteration'][not_internalized_indices] >= swell_time, ).nonzero()[0] # free fungus with REST status cells['status'][rest_indices] = FungusCellData.Status.SWOLLEN cells['iteration'][rest_indices] = 0 # free fungus with SWOLLEN status cells['status'][swollen_indices] = FungusCellData.Status.GERMINATED cells['iteration'][swollen_indices] = 0 def grow_hyphae(self, iron_min_grow, grow_time, p_branch, spacing)-
Grow fungal hyphae.
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def grow_hyphae(self, iron_min_grow, grow_time, p_branch, spacing): """Grow fungal hyphae.""" cells = self.cell_data conidia_indices = self.alive( (cells['form'] == FungusCellData.Form.CONIDIA) & (cells['status'] == FungusCellData.Status.GERMINATED) & (np.invert(cells['internalized'])) ) hyphae_indices = self.alive( (cells['form'] == FungusCellData.Form.HYPHAE) & (cells['status'] == FungusCellData.Status.GROWABLE) & (np.invert(cells['internalized'])) & (cells['iron'] > iron_min_grow) & (cells['iteration'] > grow_time) ) # grow conidia if len(conidia_indices) != 0: cells['status'][conidia_indices] = FungusCellData.Status.GROWN cells['form'][conidia_indices] = FungusCellData.Form.HYPHAE children = FungusCellData(len(conidia_indices), initialize=True) children['iron'] = cells['iron'][conidia_indices] growth = spacing * (rg.random((len(conidia_indices), 3)) * 2 - 1) children['point'] = cells['point'][conidia_indices] + growth self.spawn_hypahael_cell(children) # grow hyphae if len(hyphae_indices) != 0: cells['status'][hyphae_indices] = FungusCellData.Status.GROWN branch_mask = rg.random(len(hyphae_indices)) < p_branch not_branch_indices = (np.invert(branch_mask)).nonzero()[0] branch_indices = branch_mask.nonzero()[0] elongate_children = FungusCellData(len(hyphae_indices), initialize=True) branch_children = FungusCellData(len(branch_indices), initialize=True) elongate_children['iron'] = cells['iron'][hyphae_indices] / 2 growth = spacing * (rg.random((len(hyphae_indices), 3)) * 2 - 1) elongate_children['point'] = cells['point'][hyphae_indices] + growth if len(branch_indices) != 0: elongate_children['iron'][branch_indices] = ( cells['iron'][hyphae_indices[branch_indices]] / 3 ) branch_children['iron'] = cells['iron'][hyphae_indices[branch_indices]] / 3 growth = spacing * (rg.random((len(hyphae_indices[branch_indices]), 3)) * 2 - 1) branch_children['point'] = cells['point'][hyphae_indices[branch_indices]] + growth # update iron in orignal cells cells['iron'][hyphae_indices[not_branch_indices]] /= 2 cells['iron'][hyphae_indices[branch_indices]] /= 3 self.spawn_hypahael_cell(elongate_children) self.spawn_hypahael_cell(branch_children) def initialize_spores(self, tissue: numpy.ndarray, init_num: int)-
Initialize spores on epithelium cells.
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def initialize_spores(self, tissue: np.ndarray, init_num: int): """Initialize spores on epithelium cells.""" grid = self.grid if init_num > 0: points = np.zeros((init_num, 3)) indices = np.argwhere(tissue == TissueType.EPITHELIUM.value) if len(indices) > 0: rg.shuffle(indices) for i in range(init_num): # putting in some protection for the occasional time that we place the cell on # the boundary of the voxel-space if indices[i][2] == grid.xv.shape[0] - 1: x = grid.xv[indices[i][2]] else: x = rg.uniform(grid.xv[indices[i][2]], grid.xv[indices[i][2] + 1]) if indices[i][1] == grid.yv.shape[0] - 1: y = grid.yv[indices[i][1]] else: y = rg.uniform(grid.yv[indices[i][1]], grid.yv[indices[i][1] + 1]) if indices[i][0] == grid.zv.shape[0] - 1: z = grid.zv[indices[i][0]] else: z = rg.uniform(grid.zv[indices[i][0]], grid.zv[indices[i][0] + 1]) point = Point(x=x, y=y, z=z) points[i] = point self.spawn_spores(points) def iron_uptake(self, iron: numpy.ndarray, iron_max: float, iron_min: float, iron_absorb: float)-
Absorb iron from external environment.
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def iron_uptake(self, iron: np.ndarray, iron_max: float, iron_min: float, iron_absorb: float): """Absorb iron from external environment.""" cells = self.cell_data for vox_index in np.argwhere(iron > iron_min): vox = Voxel(x=vox_index[2], y=vox_index[1], z=vox_index[0]) cells_here = self.get_cells_in_voxel(vox) indices = [] for index in cells_here: if ( cells[index]['form'] == FungusCellData.Form.HYPHAE.value and np.invert(cells[index]['internalized']) and cells[index]['iron'] < iron_max ): indices.append(index) if len(indices) > 0: iron_split = iron_absorb * (iron[vox.z, vox.y, vox.x] / len(indices)) for cell_index in indices: cells[cell_index]['iron'] += iron_split if cells[cell_index]['iron'] > iron_max: cells[cell_index]['iron'] = iron_max iron[vox.z, vox.y, vox.x] = (1 - iron_absorb) * iron[vox.z, vox.y, vox.x] def kill(self)-
If a cell have 0 health point or out of range, kill the cell.
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def kill(self): """If a cell have 0 health point or out of range, kill the cell.""" cells = self.cell_data mask = cells.point_mask(cells['point'], self.grid) indices = self.alive(np.logical_or(cells['health'] <= 0, np.invert(mask))) cells['status'][indices] = FungusCellData.Status.DEAD cells['dead'][indices] = True def spawn_hypahael_cell(self, children)-
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def spawn_hypahael_cell(self, children): children['status'] = FungusCellData.Status.GROWABLE children['form'] = FungusCellData.Form.HYPHAE children['mobile'] = False self.extend(children) def spawn_spores(self, points)-
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def spawn_spores(self, points): n, m = points.shape if m != 3: raise ValueError('Invalid shape for a point object') spores = FungusCellData(n, initialize=True) spores['point'] = points spores['status'] = FungusCellData.Status.RESTING self.extend(spores)
Inherited members
class FungusState (*, global_state: State, cells: FungusCellList = NOTHING)-
Base type intended to store the state for simulation modules.
This class contains serialization support for basic types (float, int, str, bool) and numpy arrays of those types. Modules containing more complicated state must override the serialization mechanism with custom behavior.
Method generated by attrs for class FungusState.
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class FungusState(ModuleState): cells: FungusCellList = attr.ib(default=attr.Factory(cell_list_factory, takes_self=True)) # init_num: int = 0 # p_lodge: float = 0 # p_internal_swell: float = 0.05 # iron_min: int = 0 # iron_max: float = 0.0 # iron_absorb: float = 0.0 # spacing: float = 0.0 # iron_min_grow: float = 0.0 # grow_time: float = 0.0 # p_branch: float = 0.0 # p_internalize: float = 0.0 health: float = 100.0Ancestors
Class variables
var cells : FungusCellListvar health : float
Inherited members