Computational Ridge Identification with SCMS for Python

CRISPy is a Python library for identifying density ridges in multidimensional data using the Subspace Constrained Mean Shift (SCMS) algorithm. While tailored for astrophysics, it offers versatile 2D and 3D post-processing tools, including gridding and skeletonization of results in image space.

Visit CRISPy's documentation on Read the Docs (RTD) for detailed information on instructions, usage examples, and API details.

To install the latest version of CRISPy, clone this repository and run the following in your local directory:

    git clone https://github.com/mcyc/crispy.git
    cd crispy
    pip install -e .

For more details, please visit CRISPy's documentation.