cmb-format

CMB (Cell Model Binary) is a binary file format and Python I/O library for storing UBC GIF–style tensor and octree meshes and their associated models. It provides an alternative to the ASCII mesh and model files used by UBC GIF software. CMB supports uniform and variable-spacing tensor meshes, octree meshes, multiple named models, and file- and model-level metadata.

CMB stores mesh geometry and model values as typed arrays, with metadata in JSON, so consumers can avoid parsing millions of numbers from text. Large octree consumers that need only arrays can also avoid allocating a full consumer mesh; see the discretize round trips and benchmarks.

Capabilities

• Store mesh geometry and per-cell model arrays together in a .cmb file.
• Store models separately from geometry to avoid duplicating large meshes.
• Read individual arrays without loading the whole file.
• Verify each array's integrity with a SHA-256 checksum.

Installation

Requires Python 3.11 or newer. NumPy is the only runtime dependency. From a local checkout:

python -m pip install .

Usage

The API accepts dictionaries of NumPy arrays describing meshes and models. CMB uses a different cell ordering from UBC GIF; these routines do not convert between the two. See Cell numbering / ordering in the format specification.

Write a four-cell tensor mesh and a resistivity model, then read them back:

import numpy as np

import cmb_format as cmb

mesh = {
    "mode": "embedded",
    "mesh_class": "TensorMesh",
    "arrays": {
        "origin": np.zeros(3),
        "h_x": np.array([1.0, 2.0]),
        "h_y": np.array([1.0, 1.0]),
        "h_z": np.array([3.0]),
    },
}
models = {
    "rho": {
        "metadata": {"units": "ohm-m"},
        "array": np.array([10.0, 20.0, 30.0, 40.0]),
    }
}
cmb.write_file("example.cmb", mesh, models)

mesh, models, metadata = cmb.read_file("example.cmb")
rho = models["rho"]["array"]

read_file loads and checksum-verifies all geometry and model arrays, including nested base-mesh geometry. Its three results match write_file's mesh, models, and metadata parameters, so passing them straight back preserves the mesh geometry, model arrays, and metadata. The NumPy arrays are read-only; use .copy() if you need to modify them.

To read individual arrays without loading the whole file:

with open("example.cmb", "rb") as f:
    header, data_start = cmb.read_header(f)
    metadata = header["metadata"]
    geometry = cmb.read_arrays(f, data_start, header["mesh"]["arrays"])
    rho = cmb.read_array(f, data_start, header["models"]["rho"]["array"])

For measured large-octree and tensor round trips and timing methodology, see the discretize interoperability notes. On the measured 2.18-million-leaf sample, the generated CMB file is 10.4 MiB versus 28.8 MiB for UBC, and conversion plus CMB writing is about 21× faster.

Development

From a local checkout, with pip 25.1 or newer:

python -m pip install --group dev -e .
python -m pytest
python -m ruff check .
python -m ruff format --check .

Committed reference files in tests/goldens/ test compatibility with the binary format alongside round-trip tests.

The format specification defines the file layout and mesh schemas. Package and format versions are independent; see versioning and the package changelog.