Skip to main content

GPyTorch-QR

Supported Python Versions PyPI Version License CI CD Docs

Gaussian process quantile regression using GPyTorch.

Installation

$ pip install gpytorch-qr

Documentation

The manual can be found online:

https://gpytorch-qr.readthedocs.io

If you want to build the document yourself, get the source code and install with [doc] dependency. Then, go to doc directory and build the document:

$ pip install .[doc]
$ cd doc
$ make html

Document will be generated in build/html directory. Open index.html to see the central page.

Developing

Installation

For development features, you must install the package by pip install -e .[dev].

Configuring git

Configure the local git filter (run once after cloning):

nbstripout --install --attributes .gitattributes
git config filter.nbstripout.clean "nbstripout"
git config filter.nbstripout.smudge cat
git config filter.nbstripout.required true

Testing notebook build

Set the GPYTORCH_N_EPOCHS environment variable to 1 for quickly test notebook build.

export GPYTORCHQR_N_EPOCHS=1
jupyter nbconvert --to notebook --execute --inplace examples/*.ipynb
jupyter nbconvert --to notebook --execute --inplace examples/**/*.ipynb

Metadata

Release files for gpytorch-qr 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for gpytorch-qr 1.0.0
File Size Uploaded
gpytorch_qr-1.0.0.tar.gz 23.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for gpytorch-qr 1.0.0
File Interpreter ABI Platform
gpytorch_qr-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 41.8 kB

Release files / gpytorch_qr-1.0.0.tar.gz

Download URL gpytorch_qr-1.0.0.tar.gz
Size 23.1 kB
Tags Source
SHA-256 checksum
How to use checksums
8be30dc6d3014dfdff78eaebc01edeb271ebe122a0a5ed437bc3c9302f4aad33
BLAKE2b-256 checksum
How to use checksums
871030d6a241a1a9379d374dad35f924390a9ee140ddfba248b7cb93b8b01723
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / gpytorch_qr-1.0.0-py3-none-any.whl

Download URL gpytorch_qr-1.0.0-py3-none-any.whl
Size 18.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
9114c6c5691991e6735d4ff774cd862a703716c801e427cba78564f26e3309d8
BLAKE2b-256 checksum
How to use checksums
27ea86e15f9c8df778dda77816ccf1d4d23f7fb78caf4343c7c59425705ab957
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page