Module nlisim.modules.mip1b
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.state import State
from nlisim.util import turnover_rate
def molecule_grid_factory(self: 'MIP1BState') -> np.ndarray:
return np.zeros(shape=self.global_state.grid.shape, dtype=float)
@attr.s(kw_only=True, repr=False)
class MIP1BState(ModuleState):
grid: np.ndarray = attr.ib(
default=attr.Factory(molecule_grid_factory, takes_self=True)
) # units: atto-mols
half_life: float
half_life_multiplier: float # units: proportion
macrophage_secretion_rate: float # units: atto-mol/(cell*h)
pneumocyte_secretion_rate: float # units: atto-mol/(cell*h)
macrophage_secretion_rate_unit_t: float # units: atto-mol/(cell*step)
pneumocyte_secretion_rate_unit_t: float # units: atto-mol/(cell*step)
k_d: float # units: aM
class MIP1B(ModuleModel):
"""MIP1B"""
name = 'mip1b'
StateClass = MIP1BState
def initialize(self, state: State) -> State:
mip1b: MIP1BState = state.mip1b
# config file values
mip1b.half_life = self.config.getfloat('half_life')
mip1b.macrophage_secretion_rate = self.config.getfloat(
'macrophage_secretion_rate'
) # units: atto-mol/(cell*h)
mip1b.pneumocyte_secretion_rate = self.config.getfloat(
'pneumocyte_secretion_rate'
) # units: atto-mol/(cell*h)
mip1b.k_d = self.config.getfloat('k_d') # units: aM
# computed values
mip1b.half_life_multiplier = 0.5 ** (
self.time_step / mip1b.half_life
) # units in exponent: (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
mip1b.macrophage_secretion_rate_unit_t = mip1b.macrophage_secretion_rate * (
self.time_step / 60
)
mip1b.pneumocyte_secretion_rate_unit_t = mip1b.pneumocyte_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.pneumocyte import PneumocyteCellData, PneumocyteState
mip1b: MIP1BState = state.mip1b
molecules: MoleculesState = state.molecules
pneumocyte: PneumocyteState = state.pneumocyte
macrophage: MacrophageState = state.macrophage
grid: RectangularGrid = state.grid
# interact with pneumocytes
for pneumocyte_cell_index in pneumocyte.cells.alive():
pneumocyte_cell: PneumocyteCellData = pneumocyte.cells[pneumocyte_cell_index]
if pneumocyte_cell['tnfa']:
pneumocyte_cell_voxel: Voxel = grid.get_voxel(pneumocyte_cell['point'])
mip1b.grid[tuple(pneumocyte_cell_voxel)] += mip1b.pneumocyte_secretion_rate_unit_t
# interact with macrophages
for macrophage_cell_index in macrophage.cells.alive():
macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index]
if macrophage_cell['tnfa']:
macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point'])
mip1b.grid[tuple(macrophage_cell_voxel)] += mip1b.macrophage_secretion_rate_unit_t
# Degrade MIP1B
mip1b.grid *= mip1b.half_life_multiplier
mip1b.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 MIP1b
mip1b.grid[:] = apply_diffusion(
variable=mip1b.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
mip1b: MIP1BState = state.mip1b
voxel_volume = state.voxel_volume
mask = state.lung_tissue != TissueType.AIR
return {
'concentration (nM)': float(np.mean(mip1b.grid[mask]) / voxel_volume / 1e9),
}
def visualization_data(self, state: State):
mip1b: MIP1BState = state.mip1b
return 'molecule', mip1b.grid
Functions
def molecule_grid_factory(self: MIP1BState) ‑> numpy.ndarray
-
Expand source code
def molecule_grid_factory(self: 'MIP1BState') -> np.ndarray: return np.zeros(shape=self.global_state.grid.shape, dtype=float)
Classes
class MIP1B (config: SimulationConfig)
-
MIP1B
Expand source code
class MIP1B(ModuleModel): """MIP1B""" name = 'mip1b' StateClass = MIP1BState def initialize(self, state: State) -> State: mip1b: MIP1BState = state.mip1b # config file values mip1b.half_life = self.config.getfloat('half_life') mip1b.macrophage_secretion_rate = self.config.getfloat( 'macrophage_secretion_rate' ) # units: atto-mol/(cell*h) mip1b.pneumocyte_secretion_rate = self.config.getfloat( 'pneumocyte_secretion_rate' ) # units: atto-mol/(cell*h) mip1b.k_d = self.config.getfloat('k_d') # units: aM # computed values mip1b.half_life_multiplier = 0.5 ** ( self.time_step / mip1b.half_life ) # units in exponent: (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 mip1b.macrophage_secretion_rate_unit_t = mip1b.macrophage_secretion_rate * ( self.time_step / 60 ) mip1b.pneumocyte_secretion_rate_unit_t = mip1b.pneumocyte_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.pneumocyte import PneumocyteCellData, PneumocyteState mip1b: MIP1BState = state.mip1b molecules: MoleculesState = state.molecules pneumocyte: PneumocyteState = state.pneumocyte macrophage: MacrophageState = state.macrophage grid: RectangularGrid = state.grid # interact with pneumocytes for pneumocyte_cell_index in pneumocyte.cells.alive(): pneumocyte_cell: PneumocyteCellData = pneumocyte.cells[pneumocyte_cell_index] if pneumocyte_cell['tnfa']: pneumocyte_cell_voxel: Voxel = grid.get_voxel(pneumocyte_cell['point']) mip1b.grid[tuple(pneumocyte_cell_voxel)] += mip1b.pneumocyte_secretion_rate_unit_t # interact with macrophages for macrophage_cell_index in macrophage.cells.alive(): macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index] if macrophage_cell['tnfa']: macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point']) mip1b.grid[tuple(macrophage_cell_voxel)] += mip1b.macrophage_secretion_rate_unit_t # Degrade MIP1B mip1b.grid *= mip1b.half_life_multiplier mip1b.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 MIP1b mip1b.grid[:] = apply_diffusion( variable=mip1b.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 mip1b: MIP1BState = state.mip1b voxel_volume = state.voxel_volume mask = state.lung_tissue != TissueType.AIR return { 'concentration (nM)': float(np.mean(mip1b.grid[mask]) / voxel_volume / 1e9), } def visualization_data(self, state: State): mip1b: MIP1BState = state.mip1b return 'molecule', mip1b.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.pneumocyte import PneumocyteCellData, PneumocyteState mip1b: MIP1BState = state.mip1b molecules: MoleculesState = state.molecules pneumocyte: PneumocyteState = state.pneumocyte macrophage: MacrophageState = state.macrophage grid: RectangularGrid = state.grid # interact with pneumocytes for pneumocyte_cell_index in pneumocyte.cells.alive(): pneumocyte_cell: PneumocyteCellData = pneumocyte.cells[pneumocyte_cell_index] if pneumocyte_cell['tnfa']: pneumocyte_cell_voxel: Voxel = grid.get_voxel(pneumocyte_cell['point']) mip1b.grid[tuple(pneumocyte_cell_voxel)] += mip1b.pneumocyte_secretion_rate_unit_t # interact with macrophages for macrophage_cell_index in macrophage.cells.alive(): macrophage_cell: MacrophageCellData = macrophage.cells[macrophage_cell_index] if macrophage_cell['tnfa']: macrophage_cell_voxel: Voxel = grid.get_voxel(macrophage_cell['point']) mip1b.grid[tuple(macrophage_cell_voxel)] += mip1b.macrophage_secretion_rate_unit_t # Degrade MIP1B mip1b.grid *= mip1b.half_life_multiplier mip1b.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 MIP1b mip1b.grid[:] = apply_diffusion( variable=mip1b.grid, laplacian=molecules.laplacian, diffusivity=molecules.diffusion_constant, dt=self.time_step, ) return state
Inherited members
class MIP1BState (*, 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 MIP1BState.
Expand source code
class MIP1BState(ModuleState): grid: np.ndarray = attr.ib( default=attr.Factory(molecule_grid_factory, takes_self=True) ) # units: atto-mols half_life: float half_life_multiplier: float # units: proportion macrophage_secretion_rate: float # units: atto-mol/(cell*h) pneumocyte_secretion_rate: float # units: atto-mol/(cell*h) macrophage_secretion_rate_unit_t: float # units: atto-mol/(cell*step) pneumocyte_secretion_rate_unit_t: float # units: atto-mol/(cell*step) k_d: float # units: aM
Ancestors
Class variables
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 pneumocyte_secretion_rate : float
var pneumocyte_secretion_rate_unit_t : float
Inherited members