Python wrapper for CurveLab's 2D and 3D curvelet transforms. It uses the PyLops design framework to provide the forward and inverse curvelet transforms as matrix-free linear operations. If you are still confused, check out some examples below or the PyLops website!
Installing curvelops requires the following external components:
Both of these packages must be installed manually. See more information in
the Documentation.
After these are installed, you may install curvelops with:
export FFTW=/path/to/fftw-2.1.5
export FDCT=/path/to/CurveLab-2.1.3
python3 -m pip install git+https://github.com/PyLops/curvelops@0.23as long as you are using a pip>=10.0. To check, run python3 -m pip --version.
For a 2D transform, you can get started with:
import numpy as np
import curvelops as cl
x = np.random.randn(100, 50)
FDCT = cl.FDCT2D(dims=x.shape)
c = FDCT @ x
xinv = FDCT.H @ c
np.testing.assert_allclose(x, xinv)An excellent place to see how to use the library is the
Gallery. You can also
find more examples in the
notebooks/ folder.
- Paul Goyes has kindly contributed a rundown of how to install curvelops: link to YouTube video (in Spanish).
This package contains no CurveLab code apart from function calls. It is provided to simplify the use of CurveLab in a Python environment. Please ensure you own a CurveLab license as per required by the authors. See the CurveLab website for more information. All CurveLab rights are reserved to Emmanuel Candes, Laurent Demanet, David Donoho and Lexing Ying.
