yonder: A python package for data denoising and reconstruction
arXiv:2203.08071 · doi:10.3847/2515-5172/ac5c57
Abstract
We present a standalone implementation of a data-deconvolution method based on singular value decomposition. The tool is written in python and packaged in the open-source yonder package. yonder receives as input two matrices, one for the data and another for the errors, and outputs a denoised version of the original dataset. In this Research Note, we briefly describe the methodology and show a demonstration of the yonder on a simulated dataset.
arXiv commentSubmitted to RNAAS
References in corpus (5)
- SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
- Array Programming with NumPy
- Some Aspects of Measurement Error in Linear Regression of Astronomical Data
- Probabilistic Random Forest: A machine learning algorithm for noisy datasets
- Extreme deconvolution: Inferring complete distribution functions from noisy, heterogeneous and incomplete observations