See documentation on ReadTheDocs.

histlite is a histogram calculation and plotting library that tries to be "lite" on data structures but rich in statistics and visualization features. So far, development has taken place during my (Mike Richman) time as a graduate student and post-doctoral researcher in the field of particle astrophysics — specifically, working with the IceCube Neutrino Observatory. Histlite is intended both to facilitate high-paced exploratory data analysis as well as to serve as a building block for potentially very complex maximum likelihood data analysis implementations.

The core design considerations are:

• It must be trivial to work with and interchange between 1D, 2D, or ND histograms.
• It should be as simple as possible to perform bin-wise arithmetic operations on one or more histograms; to perform sums, integrals, etc. and thus normalizations along one or more axes simultaneously; and to perform spline or user-defined functional fits
• It should be as simple as possible to achieve publication-quality plots.

The primary histogramming functionality consists of a thin wrapper around numpy.histogramdd. Statistical tools leverage scipy but include custom solutions for some use cases. (Importantly, error propagation is currently handled manually but may be migrated to the uncertainties package in the future.) Plotting is done using matplotlib.