omfpandas.reader.OMFPandasReader

class omfpandas.reader.OMFPandasReader(filepath)

A class to read an OMF file to a pandas DataFrame.

filepath

Path to the OMF file.

Type:

Path

__init__(filepath)

Instantiate the OMFPandasReader object

Parameters:

filepath (Union[str, Path, PathLike]) – Path to the OMF file.

Methods

__init__(filepath)	Instantiate the OMFPandasReader object
find_nearest_centroid(x, y, z[, blockmodel_name])	Find the nearest centroid for provided x, y, z points using a math rounding approach considering the reference centroid.
get_bm_geometry(blockmodel_name)	Get the geometry of a BlockModel.
get_element_attribute_names(element_name)	Get the attribute names of an element.
get_element_by_name(element_name)	Get an element by its name.
plot_blockmodel(blockmodel_name, scalar[, ...])	Plot the BlockModel using PyVista.
read_block_models(blockmodel_attributes[, ...])	Return a DataFrame from multiple BlockModels.
read_blockmodel(blockmodel_name[, ...])	Return a DataFrame from a BlockModel.
view_block_model_profile(blockmodel_name[, ...])	View the profile of a BlockModel in the default web browser.

Attributes

blockmodel_attributes	Attributes for blockmodel elements, keyed by element name, including composites.
changelog	Return the change log as a DataFrame.
element_types	Dictionary of elements keyed by name

find_nearest_centroid(x, y, z, blockmodel_name=None)

Find the nearest centroid for provided x, y, z points using a math rounding approach considering the reference centroid.

Parameters:

• x (float) – X coordinate.

• y (float) – Y coordinate.

• z (float) – Z coordinate.

• blockmodel_name (Optional[str]) – The optional block model name. If not provided, the geometry for the first Tensor block model is used.

Returns:

The coordinates of the nearest centroid.

Return type:

Tuple[float, float, float]

plot_blockmodel(blockmodel_name, scalar, threshold=True, show_edges=True, show_axes=True)

Plot the BlockModel using PyVista.

Parameters:

• blockmodel_name (str) – The name of the BlockModel to plot.

• scalar (str) – The scalar to plot.

• threshold (bool) – If True, plot the thresholded mesh. Default is True.

• show_edges (bool) – If True, show the edges. Default is True.

• show_axes (bool) – If True, show the axes. Default is True.

Returns:

The PyVista plotter object.

Return type:

pv.Plotter

read_block_models(blockmodel_attributes, query=None, encode_index=False)

Return a DataFrame from multiple BlockModels.

Parameters:

• blockmodel_attributes (dict[str, list[str]]) – A dictionary of BlockModel names and the variables to include. If the dict value is None, all attributes in the blockmodel (key) are included.

• query (Optional[str]) – A query string to filter the DataFrame. Default is None.

• encode_index (bool) – If True, encode the index to a single integer.

Returns:

The DataFrame representing the merged BlockModels.

Return type:

pd.DataFrame

read_blockmodel(blockmodel_name, attributes=None, query=None, index_filter=None, encode_index=False)

Return a DataFrame from a BlockModel.

Only variables assigned to the cell (as distinct from the grid points) are loaded.

Parameters:

• blockmodel_name (str) – The name of the BlockModel to read. Use dot notation for composite (e.g., Composite.BlockModel).

• attributes (Optional[list[str]]) – The attributes/variables to include in the DataFrame. If None, all variables are included.

• query (Optional[str]) – A query string to filter the DataFrame. Default is None.

• index_filter (Optional[list[int]]) – A list of indexes to filter the DataFrame. Default is None.

• encode_index (bool) – If True, encode the index to a single integer.

Returns:

The DataFrame representing the BlockModel.

Return type:

pd.DataFrame