sigpy 0.0.1

Python package for signal reconstruction.

sigpy is a Python package for signal reconstruction, with GPU support using cupy.

sigpy provides commonly used signal processing functions, including convolution, FFT, NUFFT, wavelet transform, and thresholding functions. These operations are wrapped in a linear operator class (Linop), which allows easy manipulation, such as adjoint, addition, multiplication and composition. sigpy also implements popular iterative algorithms, such as conjugate gradient, (proximal) gradient method, primal dual hybrid gradient. All operations, except wavelet transform, can run on GPU.

sigpy also provides a submodule sigpy.mri that implements common MRI iterative reconstruction methods, including SENSE reconstruction, L1-wavelet reconstruction, and total-variation reconstruction.

Requirements

This package requires python3, numpy, scipy, pywavelets, and numba.

For optional gpu support, the package requires cupy.

For optional distributed programming support, the package requires mpi4py.

Documentation

Our documentation is hosted on readthedocs: https://sigpy.readthedocs.io