neurorosettes.grid#

Module Contents#

Classes#

UniformGrid

Class to store the objects inside a simulation container and their coordinates.

CellDensityCheck

Class to evaluate the density of a tissue around a neuron object.

OneLevelDensityCheck

Class for a cell density check based on the neighboring grid cells.

TwoLevelsDensityCheck

Class for a cell density check based on a radius of interest.
class neurorosettes.grid.UniformGrid[source]#

Class to store the objects inside a simulation container and their coordinates.

Grids are defined as uniform objects with the same size and spacing for all dimensions (2D or 3D).

property representation_grid_values: numpy.ndarray#

Returns the grid cell coordinates, inluding the top limit.

Return type:

numpy.ndarray

min: float#

The bottom limit of the grid domain size.

max: float#

The top limit of the grid domain size.

step: float#

The size of the grid cells.

use_2d: bool = True#

If a grid has a third dimension or is 2D.

grid_values: numpy.ndarray#

The coordinates of the grid cells.

idx_values: numpy.ndarray#

The indices of the grid cells.

grid: numpy.ndarray#

The grid, with the objects stored inside each cell.

__post_init__()[source]#

Creates the empty grid object based on the initial size and spacing.

Return type:

None

interpolate_idx(position)[source]#

Returns the indices of the cell where a given position should be stored.

Parameters:

position (numpy.ndarray) – The position to be located inside the grid.

Return type:

Tuple[int, int, int]

register_cell(cell)[source]#

Stores a cell object inside the grid and evaluates where to register it.

Parameters:

cell (neurorosettes.subcellular.CellBody) – The cell object to be stored inside the grid.

Return type:

None

register_neurite(neurite)[source]#

Stores a neurite object inside the grid and evaluates where to register it.

Parameters:

neurite (neurorosettes.subcellular.Neurite) – The neurite object to be stored inside the grid.

Return type:

None

remove_cell(cell)[source]#

Removes a cell object from the grid.

Parameters:

cell (neurorosettes.subcellular.CellBody) – The cell object to be removed from the grid.

Return type:

None

remove_neurite(neurite)[source]#

Removes a neurite object from the grid.

Parameters:

neurite (neurorosettes.subcellular.Neurite) – The neurite object to be removed from the grid.

Return type:

None

get_objects_in_voxel(idxx, idxy, idxz=0)[source]#

Returns the objects inside a cell of the grid.

Parameters:

  • idxx (int) – The index of the cell in the x component.

  • idxy (int) – The index of the cell in the y component.

  • idxz (int) – The index of the cell in the z component.

Return type:

A list of the cell bodies and neurites registered in the given cell of the grid.

get_close_objects(position)[source]#

Returns the objects inside a cell and its neighbors.

Parameters:

position (numpy.ndarray) – The position to be evaluated.

Returns:

  • A list of the cell bodies and objects inside a cell, and the

  • cells that surround it in 2 or 3 dimensions.

Return type:

List[Union[neurorosettes.subcellular.CellBody, neurorosettes.subcellular.Neurite]]

get_close_cells(position)[source]#

Returns only the cell bodies inside a cell and its neighbors.

Parameters:

position (numpy.ndarray) – The position to be evaluated.

Return type:

A list of the cell bodies inside a cell and its neighbors.

get_cells_in_radius(position, radius)[source]#

Returns the objects inside a radius of interest.

Parameters:

  • position (numpy.ndarray) – The position to be evaluated.

  • radius (float) – The radius of interest.

Returns:

  • A list of the cell bodies and neurites that are inside

  • a radius of interest with the given position as the centre.

Return type:

List[neurorosettes.subcellular.CellBody]

class neurorosettes.grid.CellDensityCheck[source]#

Bases: abc.ABC

Class to evaluate the density of a tissue around a neuron object.

Multiple types of checks may be defined, such as grid-based or radius-based evaluations.

abstract check_max_density(cell, grid)[source]#

Returns a true boolean value if the density around a neuron surpasses the limit.

Parameters:
Return type:

bool

class neurorosettes.grid.OneLevelDensityCheck(max_neighbors=15)[source]#

Bases: CellDensityCheck

Class for a cell density check based on the neighboring grid cells.

Parameters:

max_neighbors (int) – The maximum numbers of neighbors inside the cell grid and its neighbors.

check_max_density(cell, grid)[source]#

Checks if the number of neighbors is higher than the maximum limit.

Parameters:
Return type:

bool

class neurorosettes.grid.TwoLevelsDensityCheck(max_outer_neighbors=15, max_inner_neighbors=6, radius=18.0)[source]#

Bases: CellDensityCheck

Class for a cell density check based on a radius of interest.

Starts by checking if the number of neighbors is larger than the maximum, as done in the OneLevelDensityCheck. If this value is surpassed, the neighbors inside a radius of interest are selected and quantified. It then checks if there are more neighbors inside this radius than the expected value.

Parameters:

  • max_outer_neighbors (int) – The maximum numbers of neighbors inside the cell grid and its neighbors.

  • max_inner_neighbors (int) – The maximum number of neighbors inside of the radius of interest.

  • radius (float) – The radius of interest.

check_max_density(cell, grid)[source]#

Checks if the number of neighbors is higher than the maximum limit.

Parameters:
Return type:

bool