sigpy 0.1.7

Python package for signal reconstruction.

Source Code | Documentation | Tutorial

SigPy is a package for signal processing, with emphasis on iterative methods. It is built to operate directly on numpy arrays on CPU and cupy arrays on GPU. SigPy also provides several submodules that build on top of the core module: sigpy.plot for multi-dimensional array plotting, sigpy.mri for MRI iterative reconstruction, and sigpy.learn for dictionary learning.

Installation

SigPy requires Python version >= 3.5. The core module depends on:

• numba

• numpy

• PyWavelets

• tqdm

Additional features can be unlocked by installing the appropriate packages. To enable the plotting functions, you will need to install matplotlib. To enable CUDA support, you will need to install cupy. And to enable MPI support, you will need to install mpi4py.

Via conda

For general users, we recommend installing SigPy through conda:

conda install -c frankong sigpy
# (optional for plot support) conda install matplotlib
# (optional for CUDA support) conda install cupy
# (optional for MPI support) conda install mpi4py

Via pip

SigPy can also be installed through pip:

pip install sigpy
# (optional for plot support) pip install matplotlib
# (optional for CUDA support) pip install cupy
# (optional for MPI support) pip install mpi4py

Installation for Developers

If you want to contribute to the SigPy source code, we recommend you install it with pip in editable mode:

cd /path/to/sigpy
pip install -e .

To run tests and contribute, please install the following packages:

pip install coverage flake8 sphinx