Create xarray.DataArrays from various subsurface data formats.
Project description
gio
Geoscience I/O for grids and horizons.
The goal of this project is to load and save various geoscience surface data formats (2D and 3D seismic horizons, grids, etc). The interchange formats are the xarray.DataArray
(and xarray.Dataset
where we need a collection of arrays). This format is convenient because it allows us to store a NumPy array with Pandas-like indexing (as opposed to ordinary NumPy positional indexing).
We've started with:
- OpendTect horizons
- ZMAP grids
- Surfer grids
- Petrel horizons
What formats would you like to see? Make an issue.
Installation
This library is on PyPI, so you can install it with:
pip install gio
To get the latest unstable release, you can install it from GitHub:
python -m pip install --upgrade https://github.com/agile-geoscience/gio/archive/develop.zip
Examples
import gio
da = gio.read_surfer(fname)
da.plot()
See more examples in the notebooks folder.
Contributing
Please get involved! See CONTRIBUTING.md.
Testing
You can run the tests (requires pytest
and pytest-cov
) with
python run_tests.py
Building
This repo uses PEP 517-style packaging. Read more about this and about Python packaging in general.
Building the project requires build
, so first:
pip install build
Then to build gio
locally:
python -m build
The builds both .tar.gz
and .whl
files, either of which you can install with pip
.
© 2022 Agile Scientific, openly licenced under Apache 2.0
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