GPlib
A python library for Gaussian Process Regression.
Setup GPlib
The following packages must be installed before installing GPlib
# for ptyhon3
apt-get install python3-tk
# or for python2
apt-get install python-tkCreate and activate virtualenv (for python2) or venv (for ptyhon3)
# for ptyhon3
python3 -m venv --system-site-packages .env
# or for python2
virtualenv --system-site-packages .env
source .env/bin/activateUpgrade pip
# for ptyhon3
python3 -m pip install --upgrade pip
# or for python2
python -m pip install --upgrade pipInstall GPlib package
python -m pip install gplibUse GPlib
Generate some random data.
import numpy as np
data = {
'X': np.arange(3, 8, 1.0)[:, None],
'Y': np.random.uniform(0, 2, 5)[:, None]
}Import GPlib to use it in your python script.
import gplibInitialize the GP with the desired modules.
gp = gplib.GP(
mean_function=gplib.mea.Constant(data),
covariance_function=gplib.cov.SquaredExponential(data, is_ard=False),
likelihood_function=gplib.lik.Gaussian(),
inference_method=gplib.inf.ExactGaussian()
)Plot the GP and the data.
gplib.plot.gp_1d(gp, data)Get the posterior GP given the data.
posterior_gp = gp.get_posterior(data)Finally plot the posterior GP.
gplib.plot.gp_1d(posterior_gp, data)There are more examples in examples/ directory. Check them out!
Develop GPlib
Download the repository using git
git clone https://github.com/ibaidev/gplib.git
cd gplib
git config user.email 'MAIL'
git config user.name 'NAME'
git config credential.helper 'cache --timeout=300'
git config push.default simpleUpdate API documentation
source ./.env/bin/activate
pip install Sphinx
cd docs/
sphinx-apidoc -f -o ./ ../gplib1 maintainer
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