Gaussian processes in nonlinear least-squares fits
Project description
lsqfitgp
Module for manipulating gaussian processes. Features:
-
Use gvar to keep track transparently of correlations between prior, data and posterior.
-
Fit a latent gaussian process in a nonlinear model with lsqfit.
-
autograd-friendly.
-
Supports multidimensional structured non-numerical input with named dimensions.
-
Apply arbitrary linear transformations to the process.
-
Use dictionaries to manipulate hyperparameters and hyperpriors. Use
gvar.BufferDict
to transparently apply transformations. -
Get a covariance matrix for the optimized hyperparameters.
Installation
pip install lsqfitgp
Examples
In the directory examples
there are various scripts named with single letters
(sorry for this nonsense notation). In an IPython shell, you can run
examples/RUNALL.ipy
to run all the examples and save the figures on files.
Documentation
There's no manual, only docstrings in the code.
Tests
The test code is in tests
. Launch pytest
in the repository to run all the
tests. pytest
can be installed with pip install pytest
.
Project details
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