evo-blockmodels

GitHub source

The evo-blockmodels package provides both a low-level API client and typed Python classes for working with block models in Evo.

The full functionality of evo-blockmodels — creating, retrieving, updating attributes, running reports — is accessible directly from the BlockModel object in evo.objects.typed. When evo-blockmodels is installed, BlockModel acts as a proxy and delegates data operations to the Block Model Service automatically.

```python
from evo.objects.typed import object_from_path

# Load any block model — full evo-blockmodels functionality is available
bm = await object_from_path(manager, "my-folder/block-model")
df = await bm.to_dataframe()
await bm.add_attribute(data_df, "new_col")
report = await bm.create_report(spec)
```

Typed Block Models

The typed module provides intuitive classes for creating, retrieving, and updating regular block models with pandas DataFrame support.

Creating a block model

from evo.blockmodels.typed import RegularBlockModel, RegularBlockModelData, Point3, Size3d, Size3i

data = RegularBlockModelData(
    name="My Block Model",
    origin=Point3(0, 0, 0),
    n_blocks=Size3i(10, 10, 10),
    block_size=Size3d(1.0, 1.0, 1.0),
    cell_data=my_dataframe,
)
block_model = await RegularBlockModel.create(context, data)

Retrieving a block model

block_model = await RegularBlockModel.get(context, block_model_id)
df = block_model.cell_data  # pandas DataFrame with all cell attributes

Updating attributes

new_version = await block_model.update_attributes(
    updated_dataframe,
    new_columns=["new_col"],
)

Reports

Reports provide resource estimation summaries for block models — calculating tonnages, grades, and metal content grouped by category (e.g., geological domains, rock types).

Creating and running a report

from evo.blockmodels.typed import (
    Report, ReportSpecificationData, ReportColumnSpec, ReportCategorySpec,
    Aggregation, MassUnits, Units,
)

spec = ReportSpecificationData(
    name="Grade Report",
    category=ReportCategorySpec(column_name="domain"),
    columns=[
        ReportColumnSpec(
            column_name="Au",
            aggregation=Aggregation.MASS_AVERAGE,
            output_unit_id=Units.GRAMS_PER_TONNE,
        ),
    ],
    mass_units=MassUnits.TONNES,
)

report = await Report.create(context, block_model, spec)
result = await report.run(context)
df = result.to_dataframe()  # Tonnages and grades by domain