Merge pull request #2 from moldyn/prepare_v0.1.1

Prepare v0.1.1

CHANGELOG.md

@@ -14,13 +14,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 
 ## [Unreleased]
+
+
+## [0.1.1] - 2023-11-07
 #### Added Features and Improvements 🙌
 - Add python 3.12 support
 
+#### Other changes:
+- Slightly improved Readme and docs
+
 
 ## [0.1.0] - 2023-09-13
 - Initial release 🎉
 
 
-[Unreleased]: https://github.com/moldyn/normi/compare/v0.1.0...main
+[Unreleased]: https://github.com/moldyn/normi/compare/v0.1.1...main
+[0.1.1]: https://github.com/moldyn/normi/compare/v0.1.0...v0.1.1
 [0.1.0]: https://github.com/moldyn/normi/tree/v0.1.0

README.md

@@ -30,15 +30,15 @@
   </p>
 
   <p>
-    <a href="https://moldyn.github.io/normi">Docs</a> •
+    <a href="https://moldyn.github.io/NorMI">Docs</a> •
     <a href="#features">Features</a> •
     <a href="#installation">Installation</a> •
     <a href="#usage">Usage</a> •
-    <a href="https://moldyn.github.io/normi/faq">FAQ</a>
+    <a href="https://moldyn.github.io/NorMI/faq">FAQ</a>
   </p>
 </div>
 
-# NorMI: Nonparametric Normalized Mutual Information Estimator Based on $k$-NN Statistics
+# NorMI: Nonparametric Normalized Mutual Information Estimator Based on *k*-NN Statistics
 This software provides an extension to the Kraskov-Estimator to allow normalizing the mutual information.
 
 The method will be published soon as:
@@ -51,10 +51,9 @@ If you use this software package, please cite the above mentioned paper.
 - Intuitive usage via [module](#module---inside-a-python-script) and via [CI](#ci---usage-directly-from-the-command-line)
 - Sklearn-style API for fast integration into your Python workflow
 - No magic, only a  single parameter which can be optimized via cross-validation
-- Extensive [documentation](https://moldyn.github.io/normi) and detailed discussion in publication
+- Extensive [documentation](https://moldyn.github.io/NorMI) and detailed discussion in publication
 
 ## Installation
-<!--
 The package is called `normi` and is available via [PyPI](https://pypi.org/project/normi) or [conda](https://anaconda.org/conda-forge/normi). To install it, simply call:
 ```bash
 python3 -m pip install --upgrade normi
@@ -64,14 +63,12 @@ or
 conda install -c conda-forge normi
 ```
 or for the latest dev version
--->
-The package is not yet published and only available directly from github
 ```bash
 # via ssh key
-python3 -m pip install git+ssh://[email protected]/moldyn/normi.git
+python3 -m pip install git+ssh://[email protected]/moldyn/NorMI.git
 
 # or via password-based login
-python3 -m pip install git+https://github.com/moldyn/normi.git
+python3 -m pip install git+https://github.com/moldyn/NorMI.git
 ```
 
 ### Shell Completion
@@ -86,10 +83,16 @@ In general one can call the module directly by its entry point `$ normi` or by c
 
 ### CI - Usage Directly from the Command Line
 The module brings a rich CI using [click](https://click.palletsprojects.com).
-Each module and submodule contains a detailed help, which can be accessed by
-...
+For a complete list of all options please see the
+[docs](https://moldyn.github.io/NorMI/reference/cli/).
+```bash
+python -m normi /
+  --input input_file  / # ascii file of shape (n_samples, n_features)
+  --output output_file  / # creates ascii file of shape (n_features, n_features)
+  --n-dims / # this allows to treat every n_dims columns as a high dimensional feature
+  --verbose
 
-tba
+```
 
 ### Module - Inside a Python Script
 ```python
@@ -99,6 +102,6 @@ from normi import NormalizedMI
 # X is np.ndarray of shape (n_samples, n_features)
 
 nmi = NormalizedMI()
-nmi.fit(X)
+nmi_matrix = nmi.fit_transform(X)
 ...
 ```

docs/contributing.md

@@ -22,7 +22,7 @@ If you want to request a change, you first have to [fork the repository](https:/
 === "bash + conda"
 
     ``` bash
-    conda create -n normi -c conda-forge python
+    conda create -n normi -c conda-forge python=3.12
     conda activate normi
     python -m pip install -e .[all]
     ```
@@ -38,7 +38,7 @@ If you want to request a change, you first have to [fork the repository](https:/
 === "zsh + conda"
 
     ``` zsh
-    conda create -n normi -c conda-forge python
+    conda create -n normi -c conda-forge python=3.12
     conda activate normi
     python -m pip install -e .\[all]
     ```

docs/maintenance.md

@@ -5,15 +5,23 @@ This guide will give you an overview of how to publish a new version of normi. I
 ## Prepare New Release
 
 Please ensure that,
+
 1. the version number in `setup.py` and `src/normi/__init__.py` are bumped,
 1. a new tag is created via `git tag v0.*.*` and pushed `git push --tags`, and 
 1. the changelog includes the new tag and all changes of the release.
 
+As an example see for e.g. the commit of `v0.1.1`, [`c2582ed`](https://github.com/moldyn/NorMI/commit/c2582ed).
+
 ## Upload to PyPI
 
 There is an CI to publish new versions automatically. Therefore, a new release
 needs to be published. Please ensure that each release is based on a tag.
 
+## Build and Upload to PyPI (preferred)
+
+It is as simple as creating a new release from the new tag. The Github action
+will do the rest.
+
 ## Build and Upload to PyPI (admin only)
 
 For an introduction, please take a look at the [PyPI manual](https://packaging.python.org/en/latest/tutorials/packaging-projects/).

setup.py

@@ -58,7 +58,7 @@ def remove_gh_dark_mode_only_tags(text, tag='#gh-dark-mode-only'):
 # This call to setup() does all the work
 setuptools.setup(
     name='normi',
-    version='0.1.0',
+    version='0.1.1',
     description='Estimator for Normalized Mutual Information',
     long_description=README,
     long_description_content_type='text/markdown',

src/normi/__init__.py

@@ -8,4 +8,4 @@
 from ._estimators import NormalizedMI
 
 
-__version__ = '0.1.0'
+__version__ = '0.1.1'