Metadata-Version: 2.4
Name: splineops
Version: 0.4.6
Summary: Spline signal processing in N-D with support for GPU computing.
Project-URL: download, https://github.com/splineops/splineops.git
Project-URL: homepage, https://splineops.github.io/
Author: Dimitris Perdios, Pablo Garcia-Amorena, Philippe Thévenaz
License: BSD 3-Clause License
        
        Copyright (c) 2024, splineops
        Copyright (c) 2023-2024, EPFL (Dimitris Perdios, Pablo Garcia-Amorena)
        Copyright (c) 2021-2022, EPFL (Dimitris Perdios)
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        1. Redistributions of source code must retain the above copyright notice, this
           list of conditions and the following disclaimer.
        
        2. Redistributions in binary form must reproduce the above copyright notice,
           this list of conditions and the following disclaimer in the documentation
           and/or other materials provided with the distribution.
        
        3. Neither the name of the copyright holder nor the names of its
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License-File: LICENSE
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Requires-Dist: numpy>=1.26
Requires-Dist: scipy>=1.11
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Description-Content-Type: text/markdown

# SplineOps: Spline Operations

`splineops` is a Python-based N-dimensional signal-processing library with
support for GPU computing.

## Installation

You need at least `Python 3.10` to install `splineops` (ideally `Python 3.12`). `Python 3.11` is also compatible.

Create and activate your Python virtual environment (on Unix or MacOS)

```shell
python -m venv /path/to/splineops-env
source /path/to/splineops-env/bin/activate
```

On Windows,

```shell
python -m venv /path/to/splineops-env
./path/to/splineops-env/Scripts/Activate
```

To deactivate the environment use

```shell
deactivate
```

Minimal requirement:

```shell
pip install numpy scipy
```

Simply install `splineops` using `pip`

```shell
pip install splineops
```

To run the examples, `matplotlib`
and `IPython` (for Python UI widgets) will also be required

```shell
pip install matplotlib IPython
```

## Formatting, Type Checking, and Testing

Formatting and type checking is performed as

```shell
tox -e format
tox -e type
```

The testing requires a valid environment with a supported Python version and `tox`
installed. The tests are run with the following command (automatic pick of the
Python version)

```shell
tox
```

The tests can also be launched for a specific Python version (must match the one
installed in the active environment)

```shell
tox -e py310
tox -e py311
tox -e py312
```

*IMPORTANT:* Since CI is not implemented, make sure to run, pass, and/or fix
`tox -e format`, `tox -e type`, and `tox`.

## Packaging

Using `tox` (preferred)

```shell
tox -e build
```

Using `hatch`

```shell
hatch build -t wheel
```

## Development Environment

Easiest way to install dev dependencies

```shell
pip install numpy scipy matplotlib IPython black mypy tox hatch pytest
```

Install `splineops` development environment in editable mode

```shell
pip install -e .[dev]
```

## GPU Compatibility

You can benefit of `cupy` to deploy `splineops`. If a specific CUDA version is required, do

```shell
pip install cupy cuda-version=12.3
```

Install `splineops` cupy development environment in editable mode

```shell
pip install -e .[dev_cupy]
```

Potential other CuPy libraries
([CuPy from Conda-Forge](https://docs.cupy.dev/en/stable/install.html#installing-cupy-from-conda-forge))

```shell
pip install cupy cutensor cudnn nccl
```

## Building of the Documentation

To build the Sphinx documentation, install `splineops` doc dependencies

```shell
pip install numpy scipy matplotlib IPython sphinx sphinx-gallery sphinx-prompt sphinx-copybutton sphinx-remove-toctrees pydata-sphinx-theme sphinx-design myst-parser jupyterlite-sphinx jupyterlite-pyodide-kernel
```

Install `splineops` doc environment in editable mode

```shell
pip install -e .[docs]
```

Navigate to the `docs` directory and run the `make html` command

```shell
cd docs
make html
```

Then, go to `docs/_build/html` and open `index.html` to navigate the
documentation locally.

### Troubleshooting

If you want to make a "clean" build, go to `docs` and manually delete the folders `_build`, `auto_examples`, `gen_modules`, `notebooks_jupyterlite`, and the file `sg_execution_times.rst`.
Why isn't this done automatically? Because Sphinx optimizes speed and removes redundant tasks, by not re-creating the examples notebooks if they have already been created.
If you, for example, modify the name of the examples files, you will have to delete at least the folder `auto_examples`. Otherwise, the old examples files will not have disappeared automatically and Sphinx will raise an internal warning referring to a toctree.