grid_apps.block_models package

Submodules

grid_apps.block_models.driver module

class grid_apps.block_models.driver.Driver(params: Options | BaseParams)

Bases: Driver

Create BlockModel from parameters.

Parameters:

parameters – BlockModelOptions or InputFile containing the parameters.

static find_top_padding(obj: BlockModel, core_z_cell_size: int) → float

Loop through cell spacing and sum until core_z_cell_size is reached.

Parameters:

  • obj – Block model.

  • core_z_cell_size – Cell size in z direction.

Return pad_sum:

Top padding.

static get_block_model(workspace: Workspace, locs: ndarray, h: list, depth_core: float, pads: list, expansion_factor: float, name: str = 'BlockModel') → BlockModel

Create a BlockModel object from parameters.

Parameters:

  • workspace – Workspace.

  • locs – Location points.

  • h – Cell size(s) for the core mesh.

  • depth_core – Depth of core mesh below locs.

  • pads – len(6) Padding distances [W, E, N, S, Down, Up]

  • expansion_factor – Expansion factor for padding cells.

  • name – Block model name.

Return object_out:

Output block model.

make_grid()

Make block model object from input data.

static minimum_depth_core(locs: ndarray, depth_core: float, core_z_cell_size: int) → float

Get minimum depth core.

Parameters:

  • locs – Location points.

  • depth_core – Depth of core mesh below locs.

  • core_z_cell_size – Cell size in z direction.

Return depth_core:

Minimum depth core.

run()

Create an octree mesh from input values.

static truncate_locs_depths(locs: ndarray, depth_core: float) → ndarray

Sets locations below core to core bottom.

Parameters:

  • locs – Location points.

  • depth_core – Depth of core mesh below locs.

Return locs:

locs with depths truncated.

grid_apps.block_models.options module

class grid_apps.block_models.options.BlockModelCreationOptions(*args: Any, **kwargs: Any)

Bases: BaseModel

Block model specification parameters.

Parameters:

  • cell_size_x – Cell size in x direction.

  • cell_size_y – Cell size in y direction.

  • cell_size_z – Cell size in z direction.

  • depth_core – Depth of core mesh below locs.

  • horizontal_padding – Horizontal padding.

  • bottom_padding – Bottom padding.

  • expansion_factor – Expansion factor for padding cells.

bottom_padding: float
cell_size_x: float
cell_size_y: float
cell_size_z: float
property cell_sizes: list[float]

Cell sizes in x, y and z directions.

depth_core: float
expansion_factor: float
horizontal_padding: float
property padding: list[float]

Padding distances in west, east, south, north, down and up directions.

class grid_apps.block_models.options.BlockModelOptions(*args: Any, **kwargs: Any)

Bases: Options

Block model parameters for use with block_models.driver.

Parameters:

  • source – Source data parameters.

  • creation – Block Model creation parameters.

  • output – Block Model output parameters.

conda_environment: str = 'grid_apps'
creation: BlockModelCreationOptions
default_ui_json: ClassVar[Path] = PosixPath('/home/docs/checkouts/readthedocs.org/user_builds/mirageoscience-grid-apps/conda/stable/lib/python3.10/site-packages/grid_apps-assets/uijson/block_models.ui.json')
name: ClassVar[str] = 'block_model'
run_command: ClassVar[str] = 'grid_apps.block_models.driver'
source: BlockModelSourceOptions
title: ClassVar[str] = 'Block Model Creation'
class grid_apps.block_models.options.BlockModelOutputOptions(*args: Any, **kwargs: Any)

Bases: BaseModel

Output parameters for block model creation.

Parameters:

  • export_as – Name of the output entity.

  • out_group – Name of the output group.

export_as: str = 'block_model'
out_group: UIJsonGroup | None = None
class grid_apps.block_models.options.BlockModelSourceOptions(*args: Any, **kwargs: Any)

Bases: BaseModel

Source parameters providing input data to the driver.

Parameters:

objects – A Grid2D, Octree, BlockModel, Points, Curve or Surface source object.

objects: Points | CellObject | GridObject

Module contents