gpvecchia
Vecchia approximation routines for Gaussian Process and Data Assimilation. This code is a lightweight adaption of code from this package.
Please see the examples for particular use cases.
Documentation
Documentation is available on read the docs.
Installation
pip
pip install gpvecchia
To install a local development version
pip install -e ./
To install latest from github
pip install git+https://github.com/tide-itrh/gpvecchia.git
Features
- Vecchia-approximated Gaussian Process likelihood, prediction, prior/posterior sampling and conditional sampling, scaling to large datasets by conditioning each point on a small set of nearest neighbours instead of the full covariance matrix.
- A small library of covariance kernels (Matern 1/2, 3/2, 5/2, squared-exponential, cosine) in
gpvecchia.cov, plus anisotropic coordinate scaling and rotation. - Numba-jitted core routines, parallelised across CPU cores.
Quick Usage
import numpy as np
from gpvecchia import GPtideVecchia
from gpvecchia.cov import matern32
# Training data locations and observed values
xd = np.linspace(0, 100, 1000)[:, None]
yd = np.sin(xd[:, 0] / 5) + 0.1 * np.random.randn(1000)
# covparams = (marginal std dev, length scale)
covparams = (1.0, 5.0)
noise = 0.1
GP = GPtideVecchia(
xd, xd, noise, matern32, covparams,
order_func=np.random.permutation, order_params=len(xd),
)
mean, std = GP(yd)
See the examples for anisotropic/scaled kernels, MLE and MCMC parameter estimation, and conditional sampling.
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file gpvecchia-0.0.3.tar.gz.
File metadata
- Download URL: gpvecchia-0.0.3.tar.gz
- Upload date:
- Size: 25.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f02e0e65db9afd77ca443911b61cdc0ad1640a9d1910f4b0668621699b425b53
|
|
| MD5 |
136d0b5c943fd44c1ab1e7b6cbab9b67
|
|
| BLAKE2b-256 |
999f5775f455dd9bd9bedaaec2163e189638e7c3315a741e68e28d0163ba301b
|
Provenance
The following attestation bundles were made for gpvecchia-0.0.3.tar.gz:
Publisher:
publish.yml on TIDE-ITRH/gpvecchia
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
gpvecchia-0.0.3.tar.gz -
Subject digest:
f02e0e65db9afd77ca443911b61cdc0ad1640a9d1910f4b0668621699b425b53 - Sigstore transparency entry: 2429025440
- Sigstore integration time:
-
Permalink:
TIDE-ITRH/gpvecchia@9cc75eebcd5eb976b0937b6b7df484828dda6a66 -
Branch / Tag:
refs/tags/v0.0.3 - Owner: https://github.com/TIDE-ITRH
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@9cc75eebcd5eb976b0937b6b7df484828dda6a66 -
Trigger Event:
push
-
Statement type:
File details
Details for the file gpvecchia-0.0.3-py3-none-any.whl.
File metadata
- Download URL: gpvecchia-0.0.3-py3-none-any.whl
- Upload date:
- Size: 25.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
324427a172583f26ff2741a17ea856f4d4468e9470b34c1374b54720e565f005
|
|
| MD5 |
d6a83d5de2baffcd3362155919804c44
|
|
| BLAKE2b-256 |
7e5b373606870d3a088528fe50d4c830ae5e5af98c423e745ab12e92efd00020
|
Provenance
The following attestation bundles were made for gpvecchia-0.0.3-py3-none-any.whl:
Publisher:
publish.yml on TIDE-ITRH/gpvecchia
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
gpvecchia-0.0.3-py3-none-any.whl -
Subject digest:
324427a172583f26ff2741a17ea856f4d4468e9470b34c1374b54720e565f005 - Sigstore transparency entry: 2429025505
- Sigstore integration time:
-
Permalink:
TIDE-ITRH/gpvecchia@9cc75eebcd5eb976b0937b6b7df484828dda6a66 -
Branch / Tag:
refs/tags/v0.0.3 - Owner: https://github.com/TIDE-ITRH
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@9cc75eebcd5eb976b0937b6b7df484828dda6a66 -
Trigger Event:
push
-
Statement type:
