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Update dependencies & changes (#26)
* Update dependencies & changes * Try fix action to check changelog * ... * mailto links added malto link for each maintainer with subject title * removed banner * Shorten README.md * bump version --------- Co-authored-by: Thibaud Coroller <[email protected]>
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name: "Check Changelog Update"
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on:
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pull_request:
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branches: [ main ] # or the default branch of your repo
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jobs:
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check-changelog:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v2
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- name: Check for Changelog Updates
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run: |
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HEAD_CHANGELOG_HASH=$(git log -1 --format=format:%H -- docs/CHANGELOG.md)
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git fetch origin ${{ github.base_ref }}
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git checkout origin/${{ github.base_ref }}
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BASE_CHANGELOG_HASH=$(git log -1 --format=format:%H -- docs/CHANGELOG.md)
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if [ "$BASE_CHANGELOG_HASH" == "$HEAD_CHANGELOG_HASH" ]; then
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echo "Changelog must be updated with every pull request."
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exit 1
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fi

README.md

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# Deep survival analysis made easy
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> :warning: :construction: **We are still working on the publication of this project and appreciate your patience until everything will be ready.** :construction: :warning:
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![CodeQC](https://github.com/Novartis/torchsurv/actions/workflows/codeqc.yml/badge.svg?branch=main)
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![Docs](https://github.com/Novartis/torchsurv/actions/workflows/docs.yml/badge.svg?branch=main)
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[![PyPI - Version](https://img.shields.io/pypi/v/torchsurv)](https://pypi.org/project/torchsurv/)
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[![arXiv](https://img.shields.io/badge/arXiv-2404.10761-f9f107.svg)](https://arxiv.org/abs/2404.10761)
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[![Documentation](https://img.shields.io/badge/GithubPage-Sphinx-blue)](https://opensource.nibr.com/torchsurv/)
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[![Downloads](https://static.pepy.tech/badge/torchsurv)](https://pepy.tech/project/torchsurv)
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`TorchSurv` is a Python package that serves as a companion tool to perform deep survival modeling within the `PyTorch` environment. Unlike existing libraries that impose specific parametric forms on users, `TorchSurv` enables the use of custom `PyTorch`-based deep survival models. With its lightweight design, minimal input requirements, full `PyTorch` backend, and freedom from restrictive survival model parameterizations, `TorchSurv` facilitates efficient survival model implementation, particularly beneficial for high-dimensional input data scenarios.
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## TL;DR
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cindex.compare(cindexB)
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```
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## Installation
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## Installation and dependencies
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First, install the package:
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```bash
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pip install torchsurv
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```
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or for local installation (from package root)
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or for local installation (from package root / clone of this git repository):
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```bash
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pip install -e .
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If you use Conda, you can install requirements into a conda environment
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using the `environment.yml` file included in the `dev` subfolder of the source repository.
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Using the package has the following dependencies which will be installed automatically via pip:
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* [torch](https://pytorch.org/): Consider pre-installing if you have specific system requirements (CPU / GPU / CUDA version).
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* [scipy](https://scipy.org/): We use some statistical helper functions to calculate metrics.
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* [torchmetrics](https://lightning.ai/docs/torchmetrics/stable/): We use some statistical helper functions to calculate metrics.
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To run the tests and example notebooks, you need to install the following additional packages:
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* [lifelines](https://lifelines.readthedocs.io/en/latest/)
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* [scikit-survival](https://scikit-survival.readthedocs.io/en/stable/)
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* [pytorch_lightning](https://lightning.ai/docs/pytorch/stable/) (and [lightning](https://lightning.ai/))
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To build the documentation and for package development, please see [the development notes](https://opensource.nibr.com/torchsurv/devnotes.html) and
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[dev/environment.yml](dev/environment.yml).
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## Getting started
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We recommend starting with the [introductory guide](https://opensource.nibr.com/torchsurv/notebooks/introduction.html), where you'll find an overview of the package's functionalities.
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## Contacts
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* Thibaud Coroller [email protected] `(creator, maintainer)`
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* Mélodie Monod [email protected] `(creator, maintainer)`
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* Peter Krusche [email protected] `(author, maintainer)`
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* Qian Cao [email protected] `(author, maintainer)`
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* [Thibaud Coroller](mailto:[email protected]?subject=TorchSurv) `(creator, maintainer)`
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* [Mélodie Monod](mailto:[email protected]?subject=TorchSurv) `(creator, maintainer)`
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* [Peter Krusche](mailto:[email protected]?subject=TorchSurv) `(author, maintainer)`
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* [Qian Cao](mailto:[email protected]@novartis.com?subject=TorchSurv) `(author, maintainer)`
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If you have any questions, suggestions, or feedback, feel free to reach out the developement team [us](https://opensource.nibr.com/torchsurv/AUTHORS.html).
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docs/CHANGELOG.md

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Change log
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=========
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Version 0.1.2
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-------------
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* Updated package documentation with publication links & badges (#9, #14, #16, #19, #21, #22, #24)
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* Fixed and documented package dependencies (#1)
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Version 0.1.1
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-------------
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pyproject.toml

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[project]
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name = "torchsurv"
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version = "0.1.1"
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version = "0.1.2"
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description = "Survival analysis made easy with pytorch"
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authors = [
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{name = "Thibaud Coroller", email = "[email protected]"},
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dependencies = [
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"torch",
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"lightning",
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"scipy",
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"numpy",
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"torchmetrics",

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