Visualise a BlockModel

It is always useful to visually validate our data. In this example, we will read a block model from an OMF file and visualise it using PyVista.

import shutil
from pathlib import Path

import pandas as pd

from omfpandas import OMFPandasReader, OMFPandasWriter
from omfpandas.blockmodels.convert_blockmodel import df_to_regular_bm, blockmodel_to_df

Instantiate

Create the object OMFPandas with the path to the OMF file.

test_omf_path: Path = Path('../assets/copper_deposit.omf')
omfpr: OMFPandasReader = OMFPandasReader(filepath=test_omf_path)

We’ll inspect the elements in the omf file, and determine what volume element to convert.

omfpr.element_types

{'collar': 'PointSet', 'wolfpass_WP_assay': 'LineSet', 'Topography': 'Surface', 'Basement': 'Surface', 'Early Diorite': 'Surface', 'Intermineral diorite': 'Surface', 'Dacite': 'Surface', 'Cover': 'Surface', 'Block Model': 'TensorGridBlockModel'}

Read

We can see by inspection that we have a TensorGridBlockModel in the omf file called Block Model, so we will convert that to a Pandas DataFrame, simply for the purposes of showing the first few records.

blocks: pd.DataFrame = omfpr.read_blockmodel(blockmodel_name='Block Model', attributes=None)
print(f"DataFrame shape: {blocks.shape}")
blocks.head()

DataFrame shape: (1689600, 1)

						CU_pct
x	y	z	dx	dy	dz
5.0	5.0	5.0	10.0	10.0	10.0	0.002696
		15.0	10.0	10.0	10.0	0.002720
		25.0	10.0	10.0	10.0	0.002744
		35.0	10.0	10.0	10.0	0.002768
		45.0	10.0	10.0	10.0	0.002793

We read the block model and convert it to an OMFBlockModel object

from omfpandas.blockmodel import OMFBlockModel

bm: OMFBlockModel = OMFBlockModel(omfpr.get_element_by_name('Block Model'))

Visualise

We can visualise the block model using PyVista.

p = bm.plot(scalar='CU_pct')
p.show()

Create a regular model

# ----------------------
# We can only do this since this particular tensor model has consistent block sizes.
#
# Make a copy of the file first.

demo_omf_filepath: Path = shutil.copy2(test_omf_path, test_omf_path.with_suffix('.modified.omf'))

regular_bm = df_to_regular_bm(blockmodel_name='Regular Block Model', df=blocks.droplevel(level=['dx', 'dy', 'dz']))
regular_blocks: pd.DataFrame = blockmodel_to_df(regular_bm)

omfpw: OMFPandasWriter = OMFPandasWriter(filepath=demo_omf_filepath)
omfpw.create_blockmodel(blocks=regular_blocks, blockmodel_name='Regular Block Model')

Visualise Regular Model

bm_regular: OMFBlockModel = OMFBlockModel(omfpw.get_element_by_name('Regular Block Model'))
p = bm_regular.plot(scalar='CU_pct')
p.show()