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Author:
Jonghyun Harry Lee
License:
Copyright (c) 2018-2026, Jonghyun Lee
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that...
Summary:
A python implementation of the Principal Component Geostatistical Approach (PCGA) for large scale inversion.
Latest version:
0.3.0
Required dependencies:
covmats
|
numpy
|
scipy
Optional dependencies:
codespell
|
coverage
|
ipykernel
|
ipython
|
jupyter-sphinx
|
jupytext
|
matplotlib
|
nbsphinx
|
nbsphinx-link
|
nested-grid-plotter
|
pip
|
pre-commit
|
pre-commit-hooks
|
pydata-sphinx-theme
|
pygments
|
pypcga
|
pytest
|
pytest-cookies
|
pytest-cov
|
pytest-runner
|
ruff
|
sphinx
|
sphinx-jsonschema
|
sphinx-math-dollar
|
sphinxcontrib-bibtex
|
twine
|
ty
|
wheel
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