neurorosettes.simulation

This module deals with the neuron structure and functions

Module Contents

Classes

Timer	Class to store the simulation time data.
Container	Class that represents the environment where neurons exist.
Simulation	Class to create and run a simulation.

Functions

ccw(A, B, C)
intersect(A, B, C, D)

neurorosettes.simulation.ccw(A, B, C)

neurorosettes.simulation.intersect(A, B, C, D)

class neurorosettes.simulation.Timer

Class to store the simulation time data.

total_time: float

The total time of a simulation (in minutes).

step: float

The time between simulation points (in minutes).

current_time: float = 0.0

The current time point of the simulation.

get_progress_bar()

Returns a progress bar with the simulation time

Return type:

vedo.ProgressBar

class neurorosettes.simulation.Container(grid, simulation_2d, neuron_factory, contact_factory, drag_coefficient=10.0, density_check=None)

Class that represents the environment where neurons exist.

Parameters:

• grid (neurorosettes.grid.UniformGrid) – The grid where simulation objects will be stored, to improve neighbor interactions.

• simulation_2d (bool) – If the simulation is 2D or 3D.

• neuron_factory (neurorosettes.neurons.NeuronFactory) – The factory object to be used to create new neurons.

• contact_factory (neurorosettes.physics.ContactFactory) – The factory object to be used to create interactions.

• drag_coefficient (float) – The drag coefficient of the extracellular space.

• density_check (Optional[neurorosettes.grid.CellDensityCheck]) – Optional contact inhibition function to inhibit proliferation when the cell density is too high.

set_density_check(density_check)

Sets the contact inhibition function to be used before proliferation.

Parameters:

density_check (neurorosettes.grid.CellDensityCheck) – The contact inhibition function to be used.

Return type:

None

register_neuron(neuron, color='gray')

Registers a neuron and its representation into the container.

Parameters:

• neuron (neurorosettes.neurons.Neuron) – The new neuron to be registered.

• color – The color of the sphere that will represent the new neuron in the renderings of the simulation.

Return type:

None

update_drawings()

Updates the representations of the neurons

Return type:

None

advance_cycles(time_step)

Updates the biological clocks of every object in the simulation.

Parameters:

time_step (float) – The time between simulation time points.

Return type:

None

create_new_neuron(coordinates, outgrowth_axis=None, color='darkblue')

Creates a new neuron and registers it to the container’s grid.

The new neuron is created as an undifferentiated cell body centred at the passed coordinates. An outgrowth axis vector can be passed to model neurite outgrowth along this direction.

Parameters:

• coordinates (Union[numpy.ndarray, List[float]]) – The center position of the neuron’s cell body.

• outgrowth_axis (Optional[Union[List[float], numpy.ndarray]]) – The direction of growth of the neuron’s neurites.

• color – The color of the new neurite in the simulation renders.

Return type:

neurorosettes.neurons.Neuron

differentiate()

Checks for neurons that are flagged for differentiation and deals with differentiation

Return type:

None

kill()

Checks for neurons that are flagged for death and removes them from the container

Return type:

None

divide()

Checks for neurons that are flagged for division and deals with division

Return type:

None

get_displacement_from_force(force, time_step)

Returns the displacemnt value that a force originates, based on the equation of motion.

Parameters:

• force (numpy.ndarray) – The force value to be converted to a displacement

• time_step (float) – The time passed between simulation time points.

Return type:

numpy.ndarray

move_cell(neuron, new_coordinates)

Moves the cell to a new position and updates the proximal point of the first neurite.

Parameters:

• neuron (neurorosettes.neurons.Neuron) – The neuron object to be moved.

• new_coordinates (Union[numpy.ndarray, List[float]]) – The new coordinates to be assigned to the cell body’s centre.

Return type:

None

move_neurite(neurite, new_coordinates)

Deals with moving a neurite’s distal point and updating it on the grid.

Parameters:

• neurite (neurorosettes.subcellular.Neurite) – The neurite object to be moved.

• new_coordinates (numpy.ndarray) – The new coordinates to be assigned to the neurite’s distal point.

Return type:

None

compute_displacements(time_step)

Computes the displacement for each object based on the resulting force.

Parameters:

time_step – The time passed between simulation time points.

Return type:

None

update_cell_positions()

Updates the positions of all the simulation objects based on their velocity.

Return type:

None

solve_mechanics(time_step)

Solves the mechanical interactions and updates the neurons’ positions.

Goes through each object and computes the resulting force acting on it, then gets the object’s velocity based on the equation of motion. When all of the objects are checked, the positions are updated based on the calculated velocity.

Parameters:

time_step – The time passed between simulation time points.

Return type:

None

class neurorosettes.simulation.Simulation(timer, container)

Class to create and run a simulation.

Parameters:

• timer (Timer) – The structure to store the time data of the simulation.

• container (Container) – The structure to store the spatial data of the simulation.

run()

Runs the entire simulation by solving the mechanics at each time point.

Return type:

None

save_meshes(file_name)

Saves the neurons as PLY objects. Cell bodies are saved as spheres. Neurites are saved as cylinders.

Parameters:

file_name (str) –

Return type:

None

classmethod from_file(config_path)

Initializes a Simulation object from a YAML config file.

Parameters:

config_path (Union[pathlib.Path, str]) – The path to the YAML file config file.

Return type:

Simulation