Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix README layout #32

Merged
merged 19 commits into from
Apr 29, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension


Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions .github/workflows/pypi_upload.yml
Original file line number Diff line number Diff line change
Expand Up @@ -15,11 +15,11 @@ jobs:
name: Upload package to PyPI
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v3
with:
submodules: recursive
- name: Install Python 3
uses: actions/setup-python@v1
uses: actions/setup-python@v4
with:
python-version: 3.8
- name: Install dependencies
Expand Down
38 changes: 22 additions & 16 deletions .github/workflows/pytest.yml
Original file line number Diff line number Diff line change
Expand Up @@ -10,35 +10,41 @@ on:
jobs:
build:
runs-on: ${{ matrix.os }}
defaults:
run:
shell: bash -el {0}
strategy:
fail-fast: false
matrix:
python-version: [3.8, 3.9]
# python-version: [3.8]
# os: [ubuntu-latest, macOS-latest, windows-latest]
os: [ubuntu-latest, macOS-latest]
python-version: ["3.9", "3.10"]
os: [ubuntu-latest, macOS-latest, windows-latest]

steps:
- uses: actions/checkout@v2

- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v1
- uses: actions/checkout@v3
- name: Set up conda environment
uses: conda-incubator/setup-miniconda@v3
with:
python-version: ${{ matrix.python-version }}

auto-update-conda: true
activate-environment: test-env
auto-activate-base: false
- name: Display environment details
run: |
conda info
- name: Install dependencies
run: |
$CONDA/bin/conda config --env --append channels conda-forge
$CONDA/bin/conda env update --file requirements.txt --name base
$CONDA/bin/conda install pytest-cov
$CONDA/bin/python -m pip install --upgrade pip
$CONDA/bin/pip install -e .
conda install -c conda-forge pytest pytest-cov
conda install -c conda-forge pyfftw
python -m pip install --upgrade pip
pip install setuptools
pip install -r requirements.txt
pip install -e .
- name: Unit tests
run: |
$CONDA/bin/pytest --cov=sporco --cov-report=xml
pytest --cov=sporco --cov-report xml
- name: Upload coverage to codecov
if: matrix.os == 'ubuntu-latest'
uses: codecov/codecov-action@v2
uses: codecov/codecov-action@v3
with:
env_vars: OS,PYTHON
fail_ci_if_error: false
Expand Down
42 changes: 0 additions & 42 deletions .github/workflows/pytest_windows.yml

This file was deleted.

101 changes: 101 additions & 0 deletions README.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
[![Supported Python Versions](https://img.shields.io/pypi/pyversions/sporco.svg)](https://github.com/bwohlberg/sporco)
[![Package License](https://img.shields.io/github/license/bwohlberg/sporco.svg)](https://github.com/bwohlberg/sporco/blob/master/LICENSE)
[![Documentation Status](https://readthedocs.org/projects/sporco/badge/?version=latest)](http://sporco.readthedocs.io/en/latest/?badge=latest)
[![Test status](https://github.com/bwohlberg/sporco/actions/workflows/pytest.yml/badge.svg)](https://github.com/bwohlberg/sporco/actions/workflows/pytest.yml)
[![Test Coverage](https://codecov.io/gh/bwohlberg/sporco/branch/master/graph/badge.svg)](https://codecov.io/gh/bwohlberg/sporco)\
[![PyPi Release](https://badge.fury.io/py/sporco.svg)](https://badge.fury.io/py/sporco)
[![PyPi Downloads](https://static.pepy.tech/personalized-badge/sporco?period=total&left_color=grey&right_color=brightgreen&left_text=downloads)](https://pepy.tech/project/sporco)
[![Conda Forge Release](https://img.shields.io/conda/vn/conda-forge/sporco.svg)](https://anaconda.org/conda-forge/sporco)
[![Conda Forge Downloads](https://img.shields.io/conda/dn/conda-forge/sporco.svg)](https://anaconda.org/conda-forge/sporco)\
[![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/bwohlberg/sporco-notebooks/master?filepath=index.ipynb)
[![DOI](https://img.shields.io/badge/DOI-10.25080%2Fshinma--7f4c6e7--001-blue.svg)](https://dx.doi.org/10.25080/shinma-7f4c6e7-001)


# SParse Optimization Research COde (SPORCO)

SPORCO is a Python package for solving optimisation problems with sparsity-inducing regularisation. These consist primarily of sparse coding and dictionary learning problems, including convolutional sparse coding and dictionary learning, but there is also support for other problems such as Total Variation regularisation and Robust PCA. The optimisation algorithms in the current version are based on the Alternating Direction Method of Multipliers (ADMM) or on the Proximal Gradient Method (PGM).

If you use this software for published work, please [cite it](http://sporco.readthedocs.io/en/latest/overview.html#citing).


# Documentation

[Documentation](http://sporco.rtfd.io/) is available online, or can be built from the root directory of the source distribution by the command

python setup.py build_sphinx

in which case the HTML documentation can be found in the `build/sphinx/html` directory (the top-level document is `index.html`). Although the SPORCO package itself is compatible with Python 3.x, building the documention requires Python 3.3 or later due to the use of [Jonga](https://github.com/bwohlberg/jonga) to construct call graph images for the SPORCO optimisation class hierarchies.

An overview of the package design and functionality is also available in

> Brendt Wohlberg, [SPORCO: A Python package for standard and convolutional sparse representations](http://conference.scipy.org/proceedings/scipy2017/brendt_wohlberg.html),
> in Proceedings of the 15th Python in Science Conference, (Austin, TX, USA), doi:10.25080/shinma-7f4c6e7-001, pp. 1--8, Jul 2017


# Usage

Scripts illustrating usage of the package can be found in the `examples` directory of the source distribution. These examples can be run from the root directory of the package by, for example

python examples/scripts/sc/bpdn.py

To run these scripts prior to installing the package it will be necessary to first set the `PYTHONPATH` environment variable to include the root directory of the package. For example, in a `bash` shell

export PYTHONPATH=$PYTHONPATH:`pwd`

from the root directory of the package.

[Jupyter Notebook](http://jupyter.org/) examples are also [available](https://github.com/bwohlberg/sporco-notebooks). These examples can be viewed online via [nbviewer](https://nbviewer.jupyter.org/github/bwohlberg/sporco-notebooks/blob/master/index.ipynb), or run interactively at [binder](https://mybinder.org/v2/gh/bwohlberg/sporco-notebooks/master?filepath=index.ipynb).


# Requirements

The primary requirements are Python itself, and modules [future](http://python-future.org), [numpy](http://www.numpy.org), [scipy](https://www.scipy.org), [imageio](https://imageio.github.io/), [pyfftw](https://hgomersall.github.io/pyFFTW), and [matplotlib](http://matplotlib.org). Module [numexpr](https://github.com/pydata/numexpr) is not required, but some functions will be faster if it is installed. If module [mpldatacursor](https://github.com/joferkington/mpldatacursor) is installed, functions `plot.plot`, `plot.contour`, and `plot.imview` will support the data cursor that it provides.

Instructions for installing these requirements are provided in the [Requirements](http://sporco.rtfd.io/en/latest/install.html#requirements) section of the package documentation.


# Installation

To install the most recent release of SPORCO from [PyPI](https://pypi.python.org/pypi/sporco/) do

pip install sporco

The [development version](https://github.com/bwohlberg/sporco) on GitHub can be installed by doing

pip install git+https://github.com/bwohlberg/sporco

or by doing

git clone https://github.com/bwohlberg/sporco.git

followed by

cd sporco
python setup.py build
python setup.py install

The install commands will usually have to be performed with root privileges.

SPORCO can also be installed as a [conda](https://conda.io/docs/) package from the [conda-forge](https://conda-forge.org/) channel

conda install -c conda-forge sporco

A summary of the most significant changes between SPORCO releases can be found in the `CHANGES.rst` file. It is strongly recommended to consult this summary when updating from a previous version.


# Extensions

Some additional components of SPORCO are made available in separate repositories:

- [SPORCO-CUDA](https://github.com/bwohlberg/sporco-cuda):
GPU-accelerated versions of selected convolutional sparse coding
algorithms
- [SPORCO Notebooks](https://github.com/bwohlberg/sporco-notebooks):
Jupyter Notebook versions of the example scripts distributed with
SPORCO
- [SPORCO Extra](https://github.com/bwohlberg/sporco-extra):
Additional examples, data, and contributed code

# License

SPORCO is distributed as open-source software under a BSD 3-Clause License (see the `LICENSE` file for details).
159 changes: 0 additions & 159 deletions README.rst

This file was deleted.

1 change: 0 additions & 1 deletion requirements.txt
Original file line number Diff line number Diff line change
Expand Up @@ -4,5 +4,4 @@ scipy>=0.19.1
imageio
matplotlib>=1.3.1
pyfftw>=0.10.4
pytest-runner
pytest
Loading