mapteksdk.data.primitives.cell_properties module¶

Module containing the CellProperties Mixin class which provides support for Cell primitives.

class mapteksdk.data.primitives.cell_properties.CellProperties¶

Bases: object

A mixin class used by spatial objects to provide support for Cell Primitives.

Cell primitives are quadrilaterals defined by four points. Inheriting classes may impose restrictions on what quadrilaterals can be included in the object. See the documentation for inheriting classes for an explanation on how points are used to define cells for that object.

property major_dimension_count¶

The major dimension count of the Cell Network.

If the inheriting object is stored in row major order, then this will correspond to the row count. If stored in column major order then this will correspond to the column count.

property minor_dimension_count¶

The major dimension count of the Cell Network.

If the inheriting object is stored in row major order, then this will correspond to the column count. If stored in column major order then this will correspond to the row count.

property cells¶

This property maps the cells to the points used to define the cells. Use this to refer to the points which define the four corners of a cell.

This is a numpy array of shape (n, 4) where n is the cell count. If cells[i] is [a, b, c, d] then the four corner points of the ith cell are points[a], points[b], points[c] and points[d].

Examples

This example creates a GridSurface object with 3 rows and 3 columns of points and prints the cells. Then it prints the four points which define the first cell (index 0).

>>> from mapteksdk.project import Project
>>> from mapteksdk.data import GridSurface
>>> project = Project()
>>> with project.new("surfaces/small_square", GridSurface(
...         major_dimension_count=3, minor_dimension_count=3,
...         x_step=0.1, y_step=0.1)) as small_square:
...     print("Cells:")
...     print(small_square.cells)
...     print("The points which define the first cell are:")
...     for index in small_square.cells[0]:
...         print(f"Point {index}:", small_square.points[index])
Cells:
[[0 3 4 1]
 [1 4 5 2]
 [3 6 7 4]
 [4 7 8 5]]
The points which define the first cell are:
Point 0: [0. 0. 0.]
Point 3: [0.3 0.  0. ]
Point 4: [0.  0.1 0. ]
Point 1: [0.1 0.  0. ]

property cell_count¶

The number of cells in the cell network.

By default this is equal to the (major_dimension_count - 1) x (minor_dimension_count - 1), however subclasses may override this function to return different values.

property cell_visibility¶

The visibility of the cells as a flat array.

This array will contain cell_count booleans - one for each cell. True indicates the cell is visible and False indicates the cell is invisible.

Notes

If set to an array which is too large, the excess values will be ignored. If set to an array which is too small, this will be padded with True.

property cell_selection¶

The selection of the cells as a flat array.

This array will contain cell_count booleans - one for each cell. True indicates the cell is selected and False indicates the cell is not selected.

Notes

If set to an array which is too large, the excess values will be ignored. If set to an array which is too small, this will be padded with False.

property cell_point_count¶

The number of points in the cell network, including invalid points for which point properties are not stored. This is equal to: major_dimension_count * minor_dimension_count.

If the object contains invalid points, then cell_point_count > point_count.