Merge pull request #11 from ElementoLab/uv-migration

Uv migration and explicit LICENSE

Author: jkim810

.github/workflows/python-app.yml

@@ -1,53 +1,33 @@
-# This workflow will install Python dependencies, run tests and lint with a single version of Python
-# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
-
 name: Python application UTAG test automation
-
 on:
   push:
-    branches: [ main, dev ]
+    branches: [main, dev]
   pull_request:
-    branches: [ main, dev ]
-
+    branches: [main, dev]
 permissions:
   contents: read
-
 jobs:
   build:
-    name: every OS
+    name: Test on ${{ matrix.os }} / py${{ matrix.python-version }}
     strategy:
       matrix:
-        # run 2 copies of the current job in parallel
-        # and they will load balance all specs
-        os: ['ubuntu-latest','macos-latest'] #,  'windows-latest']
-        python-version: [3.9.19, 3.10.11]
+        os: ['ubuntu-latest', 'macos-latest']
+        python-version: ['3.12', '3.13']
       fail-fast: false
-        
     runs-on: ${{ matrix.os }}
-        
     steps:
-      # Checkout the latest code from the repo
-    - uses: actions/checkout@v3
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v3
-      with:
-        python-version: ${{ matrix.python-version }}
-      # Display the Python version being used
-    - name: Display Python version
-      run: python -c "import sys; print(sys.version)"
-      # Install the package using the setup.py
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install flake8 pytest
-        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
-        pip install .
-    - name: Lint with flake8
-      run: |
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
-    - name: Test with pytest
-      run: |
-        pytest utag/tests/utag_test.py
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+        with:
+          enable-cache: true
+
+      - name: Set up Python ${{ matrix.python-version }}
+        run: uv python install ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: uv sync --group test
+
+      - name: Test with pytest
+        run: uv run pytest utag/tests/utag_test.py

LICENSE

@@ -1,9 +1,8 @@
 # Unsupervised discovery of tissue architechture with graphs (UTAG)
-[![Zenodo badge](https://zenodo.org/badge/doi/10.1038/s41592-022-01657-2.svg)](https://doi.org/10.1038/s41592-022-01657-2) ⬅️ read the published article here <br>
-[![Biorxiv badge](https://zenodo.org/badge/doi/10.1101/2022.03.15.484534.svg)](https://doi.org/10.1101/2022.03.15.484534) ⬅️ read the preprint here <br>
-[![Zenodo badge](https://zenodo.org/badge/doi/10.5281/zenodo.6376767.svg)](https://doi.org/10.5281/zenodo.6376767) ⬅️ Preprocessed Multiplexed Image Data and UTAG results <br>
- 
- 
+[![Nature Badge](https://img.shields.io/static/v1?label=DOI&message=10.1038/s41592-022-01657-2&color=blue)](https://doi.org/10.1038/s41592-022-01657-2) ⬅️ read the published article here <br>
+[![Biorxiv Badge](https://img.shields.io/static/v1?label=DOI&message=10.1101/2022.03.15.484534&color=red)](https://doi.org/10.1101/2022.03.15.484534) ⬅️ read the preprint here <br>
+[![Zenodo Badge](https://img.shields.io/static/v1?label=DOI&message=10.5281/zenodo.6376767&color=527ea9)](https://doi.org/10.5281/zenodo.6376767) ⬅️ Preprocessed Multiplexed Image Data and UTAG results <br>
+
 This package implements segmentation of multiplexed imaging data into microanatomical domains.
 Multiplexed imaging data types are typically imaging mass cytometry (IMC), co-detection by indexing (CODEX), multiplexed ion beam imaging by time of flight (MIBI-TOF), cyclic immunofluorescence (CyCIF), and others.
 The package also provides functions for the downstream analysis of the detected micro-anatomical structure.
@@ -13,33 +12,23 @@ The package also provides functions for the downstream analysis of the detected
 
 ### Install from github
 
+With pip:
 ```bash
 pip install git+https://github.com/ElementoLab/utag.git@main
 ```
+With [`uv`](https://docs.astral.sh/uv/):
+```bash
+uv add git+https://github.com/ElementoLab/utag
+```
+
 Installation should take less than 10 seconds.
 
 #### Requirements
 There are no specific hardware requirements.
 
 Software requirements:
 - UTAG has been tested on Mac OS, Linux, and Windows [WSL](https://docs.microsoft.com/en-us/windows/wsl/about) (Windows Subsystem for Linux).
-- Python 3.9+ (tested on 3.9.19)
-- Python packages (automatically installed by `pip`):
-  - numpy
-  - pandas
-  - anndata
-  - scanpy
-  - parc
-  - squidpy
-  - scipy
-  - matplotlib
-  - tqdm
-  - networkx
-  - parmap
-  - scikit-learn
-  - setuptools_scm (may require manual installation for MacOS through pip)
-
-Specific versions of Python packages have been pinned to the [setup.cfg](setup.cfg) file.
+- Python 3.12+ (tested on 3.12)
 
 ## Tutorial
 Check out new [tutorial](documentation/UTAG%20Tutorial.ipynb) for how to run and visualize results with UTAG on your own data with minimal required input (numeric cell feature matrix and xy coordinates).
@@ -137,7 +126,7 @@ For more detailed usage of the package and downstream analysis, please refer to
 
 ## Running UTAG on R
 
-To make UTAG available to R users, we port the python code to using the `reticulate` package. The code was tested under after installing `UTAG` natively for python 3.8.10 and under conda environment with python 3.10.4, on Ubuntu 20.04.3 LTS and R 4.2.0.
+To make UTAG available to R users, we port the python code to using the `reticulate` package.
 
 Nonetheless, we highly recommend that users use our package in python for more involved analysis as the package has been developed and tested more thoroughly in python.
 
@@ -147,7 +136,6 @@ library(reticulate)
 
 # grab python interpreter
 use_python('/usr/bin/python3') # in case UTAG is installed on native python
-# use_condaenv('utag') # in case UTAG is installed using conda
 # use_virtualevn('utag') # in case UTAG is installed under virtualenv
 
 
@@ -192,3 +180,25 @@ or before by:
 ```bash
 pytest utag/tests/utag_test.py
 ```
+
+# License
+This project is licensed under the GPLv3+ license. Please see the [LICENSE](LICENSE) file for details.
+
+# Citation
+If you use UTAG in your research, please cite:
+
+```
+Kim, J., Rustam, S., Mosquera, J.M. et al. Unsupervised discovery of tissue architecture in multiplexed imaging. Nat Methods 19, 1653–1661 (2022). https://doi.org/10.1038/s41592-022-01657-2
+```
+
+```bibtex
+@article{kim2022unsupervised,
+  title={Unsupervised discovery of tissue architecture in multiplexed imaging},
+  author={Kim, Junbum and Rustam, Samir and Mosquera, Juan Miguel and Shayhiev, Renat and Rendeiro, Andre F and Elemento, Olivier},
+  journal={Nature Methods},
+  volume={19},
+  pages={1653--1661},
+  year={2022},
+  publisher={Nature Publishing Group}
+}
+```