Module nlisim.modules.tnfa
Expand source code
from typing import Any, Dict
import attr
import numpy as np
from nlisim.coordinates import Voxel
from nlisim.diffusion import apply_diffusion
from nlisim.grid import RectangularGrid
from nlisim.module import ModuleModel, ModuleState
from nlisim.modules.molecules import MoleculesState
from nlisim.random import rg
from nlisim.state import State
from nlisim.util import activation_function, turnover_rate
def molecule_grid_factory(self: 'TNFaState') -> np.ndarray:
return np.zeros(shape=self.global_state.grid.shape, dtype=float)
@attr.s(kw_only=True, repr=False)
class TNFaState(ModuleState):
grid: np.ndarray = attr.ib(
default=attr.Factory(molecule_grid_factory, takes_self=True)
) # units: atto-mol
half_life: float # units: min
half_life_multiplier: float # units: proportion
macrophage_secretion_rate: float # units: atto-mol/(cell*h)
neutrophil_secretion_rate: float # units: atto-mol/(cell*h)
epithelial_secretion_rate: float # units: atto-mol/(cell*h)
macrophage_secretion_rate_unit_t: float # units: atto-mol/(cell*step)
neutrophil_secretion_rate_unit_t: float # units: atto-mol/(cell*step)
epithelial_secretion_rate_unit_t: float # units: atto-mol/(cell*step)
k_d: float # aM
class TNFa(ModuleModel):
name = 'tnfa'
StateClass = TNFaState
def initialize(self, state: State) -> State:
tnfa: TNFaState = state.tnfa
# config file values
tnfa.half_life = self.config.getfloat('half_life') # units: min
tnfa.macrophage_secretion_rate = self.config.getfloat(
'macrophage_secretion_rate'
) # units: atto-mol/(cell*h)
tnfa.neutrophil_secretion_rate = self.config.getfloat(
'neutrophil_secretion_rate'
) # units: atto-mol/(cell*h)
tnfa.epithelial_secretion_rate = self.config.getfloat(
'epithelial_secretion_rate'
) # units: atto-mol/(cell*h)
tnfa.k_d = self.config.getfloat('k_d') # units: aM
# computed values
tnfa.half_life_multiplier = 0.5 ** (
self.time_step / tnfa.half_life
) # units: (min/step) / min -> 1/step
# time unit conversions
# units: (atto-mol * cell^-1 * h^-1 * (min * step^-1) / (min * hour^-1)
# = atto-mol * cell^-1 * step^-1
tnfa.macrophage_secretion_rate_unit_t = tnfa.macrophage_secretion_rate * (
self.time_step / 60
)
tnfa.neutrophil_secretion_rate_unit_t = tnfa.neutrophil_secretion_rate * (
self.time_step / 60
)
tnfa.epithelial_secretion_rate_unit_t = tnfa.epithelial_secretion_rate * (
self.time_step / 60
)
return state
def advance(self, state: State, previous_time: float) -> State:
"""Advance the state by a single time step."""
from nlisim.modules.macrophage import MacrophageCellData, MacrophageState
from nlisim.modules.neutrophil import NeutrophilCellData, NeutrophilState
from nlisim.modules.phagocyte import PhagocyteStatus
tnfa: TNFaState = state.tnfa
molecules: MoleculesState = state.molecules
macrophage: MacrophageState = state.macrophage
neutrophil: NeutrophilState = state.neutrophil
voxel_volume: float = state.voxel_volume
grid: RectangularGrid = state.grid
for macrophage_cell_index in macrophage.cells.alive():
macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index]
macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point'])
if macrophage_cell['status'] == PhagocyteStatus.ACTIVE:
tnfa.grid[tuple(macrophage_cell_voxel)] += tnfa.macrophage_secretion_rate_unit_t
if macrophage_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}:
if (
activation_function(
x=tnfa.grid[tuple(macrophage_cell_voxel)],
k_d=tnfa.k_d,
h=self.time_step / 60, # units: (min/step) / (min/hour)
volume=voxel_volume,
b=1,
)
> rg.uniform()
):
if macrophage_cell['status'] == PhagocyteStatus.RESTING:
macrophage_cell['status'] = PhagocyteStatus.ACTIVATING
else:
macrophage_cell['status'] = PhagocyteStatus.ACTIVE
# Note: multiple activations will reset the 'clock'
macrophage_cell['status_iteration'] = 0
macrophage_cell['tnfa'] = True
for neutrophil_cell_index in neutrophil.cells.alive():
neutrophil_cell: NeutrophilCellData = neutrophil.cells[neutrophil_cell_index]
neutrophil_cell_voxel: Voxel = grid.get_voxel(neutrophil_cell['point'])
if neutrophil_cell['status'] == PhagocyteStatus.ACTIVE:
tnfa.grid[tuple(neutrophil_cell_voxel)] += tnfa.neutrophil_secretion_rate_unit_t
if neutrophil_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}:
if (
activation_function(
x=tnfa.grid[tuple(neutrophil_cell_voxel)],
k_d=tnfa.k_d,
h=self.time_step / 60, # units: (min/step) / (min/hour)
volume=voxel_volume,
b=1,
)
> rg.uniform()
):
if neutrophil_cell['status'] == PhagocyteStatus.RESTING:
neutrophil_cell['status'] = PhagocyteStatus.ACTIVATING
else:
neutrophil_cell['status'] = PhagocyteStatus.ACTIVE
# Note: multiple activations will reset the 'clock'
neutrophil_cell['status_iteration'] = 0
neutrophil_cell['tnfa'] = True
# Degrade TNFa
tnfa.grid *= tnfa.half_life_multiplier
tnfa.grid *= turnover_rate(
x=np.array(1.0, dtype=np.float64),
x_system=0.0,
base_turnover_rate=molecules.turnover_rate,
rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
)
# Diffusion of TNFa
tnfa.grid[:] = apply_diffusion(
variable=tnfa.grid,
laplacian=molecules.laplacian,
diffusivity=molecules.diffusion_constant,
dt=self.time_step,
)
return state
def summary_stats(self, state: State) -> Dict[str, Any]:
from nlisim.util import TissueType
tnfa: TNFaState = state.tnfa
voxel_volume = state.voxel_volume
mask = state.lung_tissue != TissueType.AIR
return {
'concentration (nM)': float(np.mean(tnfa.grid[mask]) / voxel_volume / 1e9),
}
def visualization_data(self, state: State):
tnfa: TNFaState = state.tnfa
return 'molecule', tnfa.grid
Functions
def molecule_grid_factory(self: TNFaState) ‑> numpy.ndarray
-
Expand source code
def molecule_grid_factory(self: 'TNFaState') -> np.ndarray: return np.zeros(shape=self.global_state.grid.shape, dtype=float)
Classes
class TNFa (config: SimulationConfig)
-
Expand source code
class TNFa(ModuleModel): name = 'tnfa' StateClass = TNFaState def initialize(self, state: State) -> State: tnfa: TNFaState = state.tnfa # config file values tnfa.half_life = self.config.getfloat('half_life') # units: min tnfa.macrophage_secretion_rate = self.config.getfloat( 'macrophage_secretion_rate' ) # units: atto-mol/(cell*h) tnfa.neutrophil_secretion_rate = self.config.getfloat( 'neutrophil_secretion_rate' ) # units: atto-mol/(cell*h) tnfa.epithelial_secretion_rate = self.config.getfloat( 'epithelial_secretion_rate' ) # units: atto-mol/(cell*h) tnfa.k_d = self.config.getfloat('k_d') # units: aM # computed values tnfa.half_life_multiplier = 0.5 ** ( self.time_step / tnfa.half_life ) # units: (min/step) / min -> 1/step # time unit conversions # units: (atto-mol * cell^-1 * h^-1 * (min * step^-1) / (min * hour^-1) # = atto-mol * cell^-1 * step^-1 tnfa.macrophage_secretion_rate_unit_t = tnfa.macrophage_secretion_rate * ( self.time_step / 60 ) tnfa.neutrophil_secretion_rate_unit_t = tnfa.neutrophil_secretion_rate * ( self.time_step / 60 ) tnfa.epithelial_secretion_rate_unit_t = tnfa.epithelial_secretion_rate * ( self.time_step / 60 ) return state def advance(self, state: State, previous_time: float) -> State: """Advance the state by a single time step.""" from nlisim.modules.macrophage import MacrophageCellData, MacrophageState from nlisim.modules.neutrophil import NeutrophilCellData, NeutrophilState from nlisim.modules.phagocyte import PhagocyteStatus tnfa: TNFaState = state.tnfa molecules: MoleculesState = state.molecules macrophage: MacrophageState = state.macrophage neutrophil: NeutrophilState = state.neutrophil voxel_volume: float = state.voxel_volume grid: RectangularGrid = state.grid for macrophage_cell_index in macrophage.cells.alive(): macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index] macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point']) if macrophage_cell['status'] == PhagocyteStatus.ACTIVE: tnfa.grid[tuple(macrophage_cell_voxel)] += tnfa.macrophage_secretion_rate_unit_t if macrophage_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}: if ( activation_function( x=tnfa.grid[tuple(macrophage_cell_voxel)], k_d=tnfa.k_d, h=self.time_step / 60, # units: (min/step) / (min/hour) volume=voxel_volume, b=1, ) > rg.uniform() ): if macrophage_cell['status'] == PhagocyteStatus.RESTING: macrophage_cell['status'] = PhagocyteStatus.ACTIVATING else: macrophage_cell['status'] = PhagocyteStatus.ACTIVE # Note: multiple activations will reset the 'clock' macrophage_cell['status_iteration'] = 0 macrophage_cell['tnfa'] = True for neutrophil_cell_index in neutrophil.cells.alive(): neutrophil_cell: NeutrophilCellData = neutrophil.cells[neutrophil_cell_index] neutrophil_cell_voxel: Voxel = grid.get_voxel(neutrophil_cell['point']) if neutrophil_cell['status'] == PhagocyteStatus.ACTIVE: tnfa.grid[tuple(neutrophil_cell_voxel)] += tnfa.neutrophil_secretion_rate_unit_t if neutrophil_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}: if ( activation_function( x=tnfa.grid[tuple(neutrophil_cell_voxel)], k_d=tnfa.k_d, h=self.time_step / 60, # units: (min/step) / (min/hour) volume=voxel_volume, b=1, ) > rg.uniform() ): if neutrophil_cell['status'] == PhagocyteStatus.RESTING: neutrophil_cell['status'] = PhagocyteStatus.ACTIVATING else: neutrophil_cell['status'] = PhagocyteStatus.ACTIVE # Note: multiple activations will reset the 'clock' neutrophil_cell['status_iteration'] = 0 neutrophil_cell['tnfa'] = True # Degrade TNFa tnfa.grid *= tnfa.half_life_multiplier tnfa.grid *= turnover_rate( x=np.array(1.0, dtype=np.float64), x_system=0.0, base_turnover_rate=molecules.turnover_rate, rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t, ) # Diffusion of TNFa tnfa.grid[:] = apply_diffusion( variable=tnfa.grid, laplacian=molecules.laplacian, diffusivity=molecules.diffusion_constant, dt=self.time_step, ) return state def summary_stats(self, state: State) -> Dict[str, Any]: from nlisim.util import TissueType tnfa: TNFaState = state.tnfa voxel_volume = state.voxel_volume mask = state.lung_tissue != TissueType.AIR return { 'concentration (nM)': float(np.mean(tnfa.grid[mask]) / voxel_volume / 1e9), } def visualization_data(self, state: State): tnfa: TNFaState = state.tnfa return 'molecule', tnfa.grid
Ancestors
Methods
def advance(self, state: State, previous_time: float) ‑> State
-
Advance the state by a single time step.
Expand source code
def advance(self, state: State, previous_time: float) -> State: """Advance the state by a single time step.""" from nlisim.modules.macrophage import MacrophageCellData, MacrophageState from nlisim.modules.neutrophil import NeutrophilCellData, NeutrophilState from nlisim.modules.phagocyte import PhagocyteStatus tnfa: TNFaState = state.tnfa molecules: MoleculesState = state.molecules macrophage: MacrophageState = state.macrophage neutrophil: NeutrophilState = state.neutrophil voxel_volume: float = state.voxel_volume grid: RectangularGrid = state.grid for macrophage_cell_index in macrophage.cells.alive(): macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index] macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point']) if macrophage_cell['status'] == PhagocyteStatus.ACTIVE: tnfa.grid[tuple(macrophage_cell_voxel)] += tnfa.macrophage_secretion_rate_unit_t if macrophage_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}: if ( activation_function( x=tnfa.grid[tuple(macrophage_cell_voxel)], k_d=tnfa.k_d, h=self.time_step / 60, # units: (min/step) / (min/hour) volume=voxel_volume, b=1, ) > rg.uniform() ): if macrophage_cell['status'] == PhagocyteStatus.RESTING: macrophage_cell['status'] = PhagocyteStatus.ACTIVATING else: macrophage_cell['status'] = PhagocyteStatus.ACTIVE # Note: multiple activations will reset the 'clock' macrophage_cell['status_iteration'] = 0 macrophage_cell['tnfa'] = True for neutrophil_cell_index in neutrophil.cells.alive(): neutrophil_cell: NeutrophilCellData = neutrophil.cells[neutrophil_cell_index] neutrophil_cell_voxel: Voxel = grid.get_voxel(neutrophil_cell['point']) if neutrophil_cell['status'] == PhagocyteStatus.ACTIVE: tnfa.grid[tuple(neutrophil_cell_voxel)] += tnfa.neutrophil_secretion_rate_unit_t if neutrophil_cell['status'] in {PhagocyteStatus.RESTING, PhagocyteStatus.ACTIVE}: if ( activation_function( x=tnfa.grid[tuple(neutrophil_cell_voxel)], k_d=tnfa.k_d, h=self.time_step / 60, # units: (min/step) / (min/hour) volume=voxel_volume, b=1, ) > rg.uniform() ): if neutrophil_cell['status'] == PhagocyteStatus.RESTING: neutrophil_cell['status'] = PhagocyteStatus.ACTIVATING else: neutrophil_cell['status'] = PhagocyteStatus.ACTIVE # Note: multiple activations will reset the 'clock' neutrophil_cell['status_iteration'] = 0 neutrophil_cell['tnfa'] = True # Degrade TNFa tnfa.grid *= tnfa.half_life_multiplier tnfa.grid *= turnover_rate( x=np.array(1.0, dtype=np.float64), x_system=0.0, base_turnover_rate=molecules.turnover_rate, rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t, ) # Diffusion of TNFa tnfa.grid[:] = apply_diffusion( variable=tnfa.grid, laplacian=molecules.laplacian, diffusivity=molecules.diffusion_constant, dt=self.time_step, ) return state
Inherited members
class TNFaState (*, global_state: State, grid: numpy.ndarray = 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 TNFaState.
Expand source code
class TNFaState(ModuleState): grid: np.ndarray = attr.ib( default=attr.Factory(molecule_grid_factory, takes_self=True) ) # units: atto-mol half_life: float # units: min half_life_multiplier: float # units: proportion macrophage_secretion_rate: float # units: atto-mol/(cell*h) neutrophil_secretion_rate: float # units: atto-mol/(cell*h) epithelial_secretion_rate: float # units: atto-mol/(cell*h) macrophage_secretion_rate_unit_t: float # units: atto-mol/(cell*step) neutrophil_secretion_rate_unit_t: float # units: atto-mol/(cell*step) epithelial_secretion_rate_unit_t: float # units: atto-mol/(cell*step) k_d: float # aM
Ancestors
Class variables
var epithelial_secretion_rate : float
var epithelial_secretion_rate_unit_t : float
var grid : numpy.ndarray
var half_life : float
var half_life_multiplier : float
var k_d : float
var macrophage_secretion_rate : float
var macrophage_secretion_rate_unit_t : float
var neutrophil_secretion_rate : float
var neutrophil_secretion_rate_unit_t : float
Inherited members