parq_blockmodel.blockmodel.ParquetBlockModel

class parq_blockmodel.blockmodel.ParquetBlockModel(blockmodel_path, name=None, geometry=None)[source]

A class to represent a regular Parquet block model.

Block ordering is c-style, ordered by x, y, z coordinates.

blockmodel_path

The file path to the blockmodel Parquet file. This file is the source of the block model data. Consider a .pbm.parquet extension to imply a ParquetBlockModel file.

Type:: Path

name

The name of the block model, derived from the file name.

Type:: str

geometry

The geometry of the block model, derived from the Parquet file.

Type:: RegularGeometry

__init__(blockmodel_path, name=None, geometry=None)[source]

Methods

`__init__`(blockmodel_path[, name, geometry])
`create_demo_block_model`(filename[, shape, ...])	Create a demo block model with specified parameters.
`create_report`([columns, column_batch_size, ...])	Create a ydata-profiling report for the block model.
`from_geometry`(geometry, path[, name])	Create a ParquetBlockModel from a RegularGeometry object.
`from_parquet`(parquet_path[, columns, ...])	Create a ParquetBlockModel instance from a Parquet file.
`plot`(scalar[, grid_type, threshold, ...])	Plot the block model using PyVista.
`read`([columns, with_index, dense])	Read the Parquet file and return a DataFrame.
`to_dense_parquet`(filepath[, chunk_size, ...])	Save the block model to a Parquet file.
`to_pyvista`([grid_type, attributes])
`validate_sparse`()

Attributes

`centroid_index`	Get the centroid index of the block model.
`column_categorical_ordered`
`index_c`	Zero-based C-order (x, y, z) indices for the dense grid.
`index_f`	Zero-based F-order (z, y, x) indices for the dense grid.
`is_sparse`
`sparsity`

property centroid_index: MultiIndex

Get the centroid index of the block model.

Returns:: The MultiIndex representing the centroid coordinates (x, y, z).
Return type:: pd.MultiIndex

classmethod create_demo_block_model(filename, shape=(3, 3, 3), block_size=(1, 1, 1), corner=(-0.5, -0.5, -0.5), axis_azimuth=0.0, axis_dip=0.0, axis_plunge=0.0)[source]

Create a demo block model with specified parameters.

Parameters:

filename (Path) – The file path where the Parquet file will be saved.
shape (tuple) – The shape of the block model.
block_size (tuple) – The size of each block.
corner (tuple) – The coordinates of the corner of the block model.
axis_azimuth (float) – The azimuth angle in degrees for rotation.
axis_dip (float) – The dip angle in degrees for rotation.
axis_plunge (float) – The plunge angle in degrees for rotation.

Returns:

An instance of ParquetBlockModel with demo data.

Return type:

ParquetBlockModel

create_report(columns=None, column_batch_size=10, show_progress=True, open_in_browser=False)[source]

Create a ydata-profiling report for the block model. The report will be of the same name as the block model, with a ‘.html’ extension.

Parameters:

columns (Optional[list[str]]) – List of column names to include in the profile. If None, all columns are used.
column_batch_size (int) – The number of columns to process in each batch. If None, processes all columns at once.
show_progress (bool) – bool: If True, displays a progress bar during profiling.
open_in_browser (bool) – bool: If True, opens the report in a web browser after generation.

Return type:

Path

Returns: Path: The path to the generated profile report.

classmethod from_geometry(geometry, path, name=None)[source]

Create a ParquetBlockModel from a RegularGeometry object.

The model will have no attributes.

Parameters:

geometry (RegularGeometry) – The geometry of the block model.
path (Path) – The file path where the Parquet file will be saved.
name (Optional[str]) – The name of the block model. If None, the name will be derived from the path.

Returns:

An instance of ParquetBlockModel with the specified geometry.

Return type:

ParquetBlockModel

classmethod from_parquet(parquet_path, columns=None, overwrite=False, axis_azimuth=0.0, axis_dip=0.0, axis_plunge=0.0)[source]

Create a ParquetBlockModel instance from a Parquet file.

Parameters:

parquet_path (Path) – The path to the Parquet file.
columns (Optional[list[str]]) – The list of columns to extract from the Parquet file.
overwrite (bool) – If True, allows overwriting an existing ParquetBlockModel file. Defaults to False.
axis_azimuth (float) – The azimuth angle in degrees for rotation. Defaults to 0.0.
axis_dip (float) – The dip angle in degrees for rotation. Defaults to 0.0.
axis_plunge (float) – The plunge angle in degrees for rotation. Defaults to 0.0.

Return type:

ParquetBlockModel

property index_c: ndarray: Zero-based C-order (x, y, z) indices for the dense grid.

property index_f: ndarray: Zero-based F-order (z, y, x) indices for the dense grid.

plot(scalar, grid_type='image', threshold=True, show_edges=True, show_axes=True, enable_picking=False, picked_attributes=None)[source]

Plot the block model using PyVista.

Parameters:

scalar (str) – The name of the scalar attribute to visualize.
grid_type (Literal['image', 'structured', 'unstructured']) – The type of grid to use for plotting. Options are “image”, “structured”, or “unstructured”.
threshold (bool) – The thresholding option for the mesh. If True, applies a threshold to the scalar values.
show_edges (bool) – Show edges of the mesh.
show_axes (bool) – Show the axes in the plot.
enable_picking (bool) – If True, enables picking mode to interactively select cells in the plot.
picked_attributes (Optional[list[str]]) – A list of attributes that will be returned in picking mode. If None, all attributes are returned.

Return type:

Plotter

Returns:

read(columns=None, with_index=True, dense=False)[source]

Read the Parquet file and return a DataFrame.

Parameters:

columns (Optional[list[str]]) – List of column names to read. If None, all columns are read.
with_index (bool) – If True, includes the index (‘x’, ‘y’, ‘z’) in the DataFrame.
dense (bool) – If True, reads the data as a dense grid. If False, reads the data as a sparse grid.

Returns:

The DataFrame containing the block model data.

Return type:

pd.DataFrame

to_dense_parquet(filepath, chunk_size=100000, show_progress=False)[source]

Save the block model to a Parquet file.

This method saves the block model as a Parquet file by chunk. If dense is True, it saves the block model as a dense grid, :type filepath: Path :param filepath: The file path where the Parquet file will be saved. :type filepath: Path :type chunk_size: int :param chunk_size: The number of blocks to save in each chunk. Defaults to 100_000. :type chunk_size: int :type show_progress: bool :param show_progress: If True, show a progress bar. Defaults to False. :type show_progress: bool

Return type:: None